Intelligent decision-making cockpit construction method based on reinforcement learning

Abstract

The invention discloses an intelligent decision-making cockpit construction method based on reinforcement learning, particularly relates to the technical field of artificial intelligence and computer data processing, and is used for solving the problem that in a non-stable scene with return delay and business constraint, the decision-making cockpit is not stable. The problems that the reinforcement learning strategy is difficult to stabilize and meet the standard due to the fact that the time sequence is inconsistent with the index caliber, reward settlement and evaluation are disjointed and online admission lacks an auditing threshold and a backspacing closed loop are solved. By establishing a deterministic time sequence of a double-anchor time base and an idempotent key, a key index caliber is compiled into an executable reward byte code and is frozen and played back when drifting is triggered, a debit and credit account book is rewarded to close a delay return link, and then a debit and credit account book is rewarded by matching feasible region projection and distribution external suppression of action grammar. And gray scale amplification gating is implemented by using a combination threshold of the three types of lower boundaries, so that an executable decision can still be stably, compliantly and audibly output in a non-stable scene with return delay and constraint boundaries.

Description

Technical Field

[0001] This invention relates to the fields of artificial intelligence and computer data processing technology, specifically to a method for constructing an intelligent decision-making cockpit based on reinforcement learning. Background Technology

[0002] In business operations such as marketing scheduling, supply chain takt time, risk control limits, and equipment maintenance, the industry often uses reinforcement learning or heuristic optimization to build a "decision cockpit." Existing systems generally collect data from multiple asynchronous platforms (business systems, monitoring systems, log systems), often using a single time synchronization caliber and a "best effort" stack access, with event order depending on arrival time or simple deduplication. Rewards often directly reference BI metrics or report definitions, and with rhythm adjustments, rule revisions, and regional differences in caliber, inconsistencies often arise between offline training and online evaluation. Reward settlement often uses window aggregation instead of delayed attribution, lacking unified settlement and reconciliation for delayed rewards. In the evaluation phase, common practices rely on experience playback or offline evaluation based on importance sampling, but lack a unified quality threshold and stability boundary, resulting in limited robustness to distribution drift and outlier samples.

[0003] In the deployment phase, existing methods often use manual thresholds, A / B switching, or simple rate limiting as entry barriers. Constraints and compliance are mostly implemented through blacklists, whitelists, or offline rules collectively displayed on the outer layer of the strategy. There is a lack of systematic constraints on the feasible domain verification, mutual exclusion resolution, and interval pruning of the strategy output. Deployment and scaling lack an integrated entry boundary and scaling mechanism with evaluation criteria. When encountering fluctuations or defaults, manual rollbacks or coarse-grained rollbacks are often relied upon, making it difficult to form a verifiable and traceable closed-loop audit chain. The direct consequences of this are: drifting of indicator criteria leading to reward leakage and evaluation bias; delayed rewards and out-of-distribution samples making learning and evaluation unstable; lack of unified lower bound guarantees and evidence retention for deployment entry; unclear rollback and restart conditions; and difficulty in stably implementing compliance boundaries and service level restrictions.

[0004] Based on the above situation, how can we build a unified time-series alignment and reward settlement mechanism in scenarios where instability, delayed returns, and business constraints coexist? On this basis, we can form an auditable closed loop for online access and gray-scale rollout, ensuring that the evaluation criteria are consistent with the online criteria, constraints are stably executed, and online and rollback processes are traceable and verifiable? Summary of the Invention

[0005] (a) Technical problems to be solved

[0006] To address the shortcomings of existing technologies, this invention provides a method for constructing an intelligent decision-making cockpit based on reinforcement learning, thereby solving the problems mentioned in the background section.

[0007] (II) Technical Solution

[0008] To achieve the above objectives, the present invention provides the following technical solution: a method for constructing an intelligent decision-making cockpit based on reinforcement learning, comprising: S1. Establish a dual-anchor time base, set up a disordered buffer and water level line, generate idempotent keys according to equipment identification, time anchor, window order, template version, and feature signature, solidify events and label quality quadruples; S2. Construct a key indicator caliber map and compile it into reward bytecode, including time window, delay compensation and weight fingerprint, set a drift threshold, trigger caliber switching and freeze playback; S3. Establish a reward loan ledger, register debt notes, construct forward and backward traces, settle rewards according to reward bytecode in the delay window, and weight samples according to quality quadruples. S4, compliance rules and service level thresholds are compiled into action syntax, and the policy output is subjected to syntax verification, interval pruning, mutual exclusion resolution and feasible region projection. Barrier functions and budget Lagrange updates are introduced, and multipliers converge according to the cooling curve. S5. Set up an out-of-bounds detector, determine out-of-bounds based on feature covariance radius and kernel distance, perform confidence reduction and target network mildening on out-of-bounds samples, and combine with order preservation truncation. Playback only accepts samples that meet the quality threshold. S6. Calculate the lower bound of importance sampling, robustness, and empirical risk, set a conjunctive threshold, advance the flow according to quantiles when the threshold is reached, and back off when the constraint exceeds the limit. Generate an audit index to solidify the decision and the flow trajectory.

[0009] Furthermore, S1 includes: Establish a dual-anchor time base under the locked ledger version, and register the time synchronization source, calibration cycle and tolerance; Set up a disordered buffer and proceed according to the water level line; Generate idempotent keys based on device identifier, time anchor, window order, template version, and signature. When the window coverage reaches the water level, the event is written to the event store in append-only mode using the idempotent key, the evidence chain hash is calculated, and the audit index is generated and registered. The quality quadruple is registered simultaneously, including completeness, freshness, consistency, and credibility; Playback of late events during the buffer period; playback after the buffer period; retransmission of events after the buffer period. Audited and locked records are transferred to the isolation zone and registered for review tasks, without rewriting the original fixed records.

[0010] Furthermore, S2 includes:

[0011] Based on the ledger, a caliber map is generated and compiled into reward bytecode. The reward bytecode consists of a time window, latency compensation, and weight fingerprint. The start and end of the time window are determined by the dual-anchor time base.

[0012] The reward bytecode is stored in a read-only area and version locked, and is uniquely controlled by an idempotent key consisting of a fixed combination of the caliber version and the effective time.

[0013] When a version change occurs, a change order and signature hash are generated and written into the evidence chain;

[0014] The read-only area adopts a single-master sequential commit and version number comparison strategy. If the commit fails, an idempotent key-based backoff retry is performed. If the retry fails, the version is rolled back to the previous effective version.

[0015] Furthermore, a drift threshold and trigger count are set, and the similarity and stability of the weighted fingerprints within adjacent time windows are continuously monitored. When the drift trigger condition is met, a caliber switching event is released and the corresponding replay window is frozen.

[0016] The playback window is read-only and maintains the idempotent key order; no new entries, deletions, or skipping are allowed.

[0017] After the new version passes stability and consistency checks during the continuous observation period, it will be unfrozen in chronological order.

[0018] Changes are distributed through the intranet configuration channel and confirmed by the subscriber. If confirmation is not completed, the system will enter the rollback path.

[0019] The entire process of freezing and unfreezing is written into the chain of evidence and records the version of the statement, the effective time, and the freezing mark.

[0020] Furthermore, S3 includes:

[0021] Establish a reward and loan ledger on a unified time-based event stream, register debt notes when strategy actions are generated, and uniquely associate actions with arrival states using idempotent keys;

[0022] When the delay window expires, the reward is settled based on the reward bytecode, and the accounting is recorded according to the weight of the quality quadruple mapped by the hierarchical table;

[0023] Write the reconciliation list to the ledger's dedicated area in an append-only manner and create an idempotent key index and a ledger sequence index;

[0024] When an idempotent key conflict occurs, the first record to arrive is fixed, and the later record is not duplicated. The conflict factor is registered, the quality quadruple label is changed by adding an entry, and the evidence chain record is registered in the audit storage.

[0025] Version locking is implemented for the reward bytecode and the tiered table, and change records are written to the audit storage.

[0026] Furthermore, S4 includes:

[0027] Under dual-anchor time base and idempotent key constraints, the compliance list, service level thresholds and physical boundaries are compiled into action syntax;

[0028] Output the data using a processing strategy that proceeds in the order of syntax checking, interval pruning, mutual exclusion resolution, and feasible region projection.

[0029] Within a feasible set that simultaneously satisfies the compliance list, service level thresholds, and physical boundaries, nearest neighbors are determined based on a weighted distance metric locked by the action syntax version.

[0030] The constraint strength is updated along the cooling curve using a budget multiplier.

[0031] Write the decision record into the decision area and lock the order with time anchors and fragment numbers. Record the action syntax version, feasible region projection result, budget value, multiplier trajectory, time anchor, idempotent key and signature hash.

[0032] Furthermore, S5 includes:

[0033] Set up an out-of-bounds detector and synthesize the feature covariance range and kernel distance in a unified feature space as the out-of-bounds degree;

[0034] The covariance range is determined by a stable subset that meets the quality quadruple threshold and is based on the previous version's caliber.

[0035] When the out-of-bounds degree reaches the out-of-bounds judgment, confidence reduction is applied to the sample, smoothing is applied to the target parameter copy, and monotonicity truncation is applied to the parameter update.

[0036] Only samples that meet the playback quality threshold are allowed into the playback buffer;

[0037] The sample index area records the bounds, confidence reduction flags, target parameter copy smoothing level, and monotonicity truncation flags using idempotent keys as the primary key, and writes them to the audit storage with version locking.

[0038] Furthermore, S6 includes:

[0039] Within a fixed observation window, the sampling weight truncation lower bound, robust lower bound, and empirical risk lower bound are calculated. The statistical caliber, quality threshold, and window range of the three types of lower bounds are consistent.

[0040] Set a concurrency threshold and perform admission determination in the order of first checking the constraint budget and then comparing the three types of lower bounds;

[0041] If the concurrency threshold is not met, the baseline strategy is executed, and the rejection reason, time anchor, and threshold version are recorded in the audit index.

[0042] The budget default predictor, statistical caliber, and baseline revenue threshold are version-locked, and the version identifier is recorded in the audit index.

[0043] Furthermore, after the aforementioned admission determination is passed, the gray-scale phased advancement is implemented in a segmented sequence, with an independent resource pool executing the decision and setting an end-to-end latency limit;

[0044] The write order is locked by time anchors and segmented sequences, and the adjudication record is uniquely fixed by idempotent keys;

[0045] If any constraint goes out of bounds, the strategy is reverted to the baseline and the revert factor is recorded.

[0046] The audit index records the threshold for concatenation, the details of the three types of lower bounds, the start and end points of the window and the sliding step size, the quality threshold, the gray-scale rollout plan, the volume increase trajectory, the rollback factor, the signature hash and the version identifier.

[0047] Compared with the prior art, the present invention has the following beneficial effects: 1. By establishing a deterministic timing sequence with dual anchor time bases and idempotent keys, compiling key indicator definitions into executable reward bytecode and freezing replay when drift is triggered, closing the delayed reward chain with a reward lending ledger, and combining feasible domain projection and out-of-distribution suppression with action syntax, as well as implementing gray-scale scaling gating with conjunctive thresholds of three types of lower bounds, it is possible to achieve stable, compliant, and auditable output of executable decisions in scenarios that are non-stationary and have reward delays and constraint boundaries. 2. By advancing the water level and adding storage lock order and idempotency, solidifying the whole chain decision with audit indexes and evidence chains, advancing and rolling back the closed-loop online process with gray-scale phased deployment, and using version locking to run through the standards, syntax and models, we can achieve controllable timing, traceable policies and rapid recovery in engineering deployment, and improve the replicability and compliance implementation capabilities in multi-tenant and cross-domain scenarios. Attached Figure Description

[0048] Figure 1 This is a flowchart illustrating a method for constructing an intelligent decision-making cockpit based on reinforcement learning according to the present invention. Detailed Implementation

[0049] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] Example: Figure 1 A flowchart illustrating a reinforcement learning-based intelligent decision-making cockpit construction method of the present invention is provided. The method includes:

[0051] S1. Establish a dual-anchor time base, set up a disordered buffer and water level line, generate idempotent keys according to equipment identification, time anchor, window order, template version, and feature signature, solidify events and label quality quadruples;

[0052] S2. Construct a key indicator caliber map and compile it into reward bytecode, including time window, delay compensation and weight fingerprint, set a drift threshold, trigger caliber switching and freeze playback;

[0053] S3. Establish a reward loan ledger, register debt notes, construct forward and backward traces, settle rewards according to reward bytecode in the delay window, and weight samples according to quality quadruples.

[0054] S4, compliance rules and service level thresholds are compiled into action syntax, and the policy output is subjected to syntax verification, interval pruning, mutual exclusion resolution and feasible region projection. Barrier functions and budget Lagrange updates are introduced, and multipliers converge according to the cooling curve.

[0055] S5. Set up an out-of-bounds detector, determine out-of-bounds based on feature covariance radius and kernel distance, perform confidence reduction and target network mildening on out-of-bounds samples, and combine with order preservation truncation. Playback only accepts samples that meet the quality threshold.

[0056] S6. Calculate the lower bound of importance sampling, robustness, and empirical risk, set a conjunctive threshold, advance the flow according to quantiles when the threshold is reached, and back off when the constraint exceeds the limit. Generate an audit index to solidify the decision and the flow trajectory.

[0057] The technical connections and implementation logic of the six steps are as follows:

[0058] S1 first establishes a dual-anchor time base on-site using equipment and communication time synchronization, configuring out-of-order buffers and water level lines. Based on equipment identifiers, time anchors, window order, template versions, and feature signatures, it generates idempotent keys and solidifies events, while simultaneously labeling quality quadruples to establish a unified time series, deduplication, and retrieval benchmark for subsequent stages. Building upon this, S2 compiles the values ​​of key indicators into executable reward bytecode according to a unified ledger, setting drift thresholds and freeze replay to ensure the reward caliber remains stable and traceable over time windows. Subsequently, S3 uses idempotent keys to associate policy actions with arrival states, establishing a reward debit / credit ledger and settling returns according to the reward bytecode within the delay window, forming verifiable forward and backward traces to provide reconciliation basis for evaluation and retraining. For the execution end, S4 compiles compliance rules and service level thresholds into action syntax, sequentially performing syntax verification, interval pruning, mutual exclusion resolution, and feasible region projection on the policy output, and then using budget multipliers according to the cooling curve. Line convergence ensures that each action falls within the feasible region and the constraint strength is controllable. To suppress the impact of distribution drift on learning and evaluation, S5 sets up an out-of-distribution detector before the training and playback paths, using the feature covariance radius and kernel distance to jointly determine out-of-bounds errors. For out-of-bounds samples, confidence reduction, target network mildening, and order-preserving truncation are performed, and only samples that meet the quality threshold are accepted for playback, stabilizing estimation fluctuations from the source. Finally, S6 calculates the lower bound of truncation importance sampling, robustness lower bound, and empirical risk lower bound within an hourly observation window, sets a conjunction threshold, and advances the flow according to quantile grayscale. If any constraint exceeds the boundary, it reverts to the baseline strategy, and at the same time, the decision and the flow trajectory are solidified with an audit index. The above decision results and revert factors are recorded in reverse to the evidence chain and ledger version, driving the caliber stabilization of S2, the settlement consistency of S3, the constraint adjustment of S4, and the quality threshold of S5 to converge in synergy, thereby forming a closed-loop implementation logic with tight connection between the preceding and following steps and a clear causal path.

[0059] S1. Establish a dual-anchor time base, set up a randomized buffer and water level line, generate idempotent keys according to equipment identifier, time anchor, window order, template version, and feature signature, solidify events and label quality quadruples. The specific implementation is as follows:

[0060] In sites equipped with both device and communication time synchronization, a unified time base (dual-anchor time base) is first established using both time synchronization methods. Device time synchronization uses the device's own clock as the reference, while communication time synchronization uses the network-side time synchronization reference. The source, calibration cycle, and tolerances of both are clearly defined in the ledger. Systematic deviations are eliminated using alignment rules, and time synchronization alignment stamps and tolerance limits are recorded. The ledger is a read-only configuration library containing field specification templates, time synchronization strategies, window and waterline parameters, quality assessment rules, message channel semantics, access control, and retention policies. Version locking is employed, and an evidence chain is created using approval records, change orders, and signature hashes.

[0061] To stabilize the arrival order of events, a disordered buffer is set up to temporarily store early or late events, and a water level line is used as the boundary for the window to reach a solidified state. The window length and water level line step size are standardized in the ledger. The water level line step size does not exceed and is divisible by the window length. If not configured, the window length can be set to one minute and the water level line step size can be set to one second. The window sequence is a natural sequence number that increments according to the time anchor. When crossing days or restarting, it continues to increment according to the ledger's reset strategy or is reset to zero in batches and is included in version locking. The field specification template gives a default unit and collection rhythm for each field. Fields that are not configured use the template default items and the reason for using them is written into the evidence chain.

[0062] Before deployment, time synchronization alignment, noise suppression, and field completion are performed to ensure consistent event output from various devices under the same time base. When window coverage reaches a certain threshold, events within the window are permanently stored. A time anchor, used to pinpoint event timing within the window, consists of a time source identifier, a time synchronization alignment stamp, and a calibration batch identifier. The field order is fixed, and default values ​​and ranges are version-locked in the ledger. To ensure idempotency and traceability, an idempotent key is generated by combining device identifier, time anchor, window order, template version, and feature signature. This idempotent key uniquely identifies the window event set and is used for deduplication and playback correction. The feature signature is generated by a standardized sequence of key fields within the window using a unified hash function. The hash length can be set to a fixed length. In case of a collision, a sequence number salt is added without altering the business fields, and the mapping relationship is written into the evidence chain.

[0063] Each solidified record is simultaneously labeled with a quality quadruple, which consists of completeness, freshness, consistency, and credibility: completeness is scored in segments based on field missing rate, freshness is scored in segments based on arrival delay, consistency is scored based on the consistency ratio of multi-source fields, and credibility is scored in segments based on timing stability and link jitter. Segment thresholds and default values ​​are locked in the version of the ledger. Solidified records are written to the event storage in an append-only manner. The event storage supports retrieval by window index and idempotent key, and calculates the evidence chain hash during writing. The evidence chain hash generates a summary for key fields and concatenates them to form an audit index for subsequent review. The retention period can be set to no less than twelve months, and the anonymization granularity is performed at the field level. The length of the evidence chain hash can be set to a fixed length, and the value range is locked in the version of the ledger. Preferably, the length can be set to 256 bits or 512 bits. The least privilege policy is limited to the field and operation granularity, and unauthorized writes and version rollbacks are rejected by default. All authorizations and accesses are recorded in the audit trail and included in the retention period.

[0064] Upstream events are pushed via local bus or lightweight message channels. Message channel semantics require at least one delivery, and idempotent deduplication ensures no duplicate entries into the database. When a channel is downgraded, it switches to a batch retransmission and replay channel while maintaining the idempotent strategy. When a channel recovers from downgrade to the main channel, the recovery time and incomplete retransmission list are registered in the evidence chain, cleared, and the progress rhythm resumed. Downstream data is pulled according to idempotent keys and window order, following a waterline-based advance locking strategy, and reads are not read outside the window. To meet online decision-making time limits, an end-to-end latency budget is set, and upper limits are allocated in four stages: timing alignment, buffering and advancement, solidification and writing, and audit hashing. Specific upper limit values ​​are configured in the ledger and included in version locking. To ensure throughput, sharding parallelism and backoff retries are adopted. Sharding rules are based on device identifiers and window order. The maximum number of retries is limited. If the upper limit is exceeded, the failure reason and key value are recorded and placed in an isolated partition for subsequent repair through the retransmission and replay mechanism.

[0065] Sequential control is based on the water level progression. When a late event is within the buffer period, playback correction is performed and the correction factor is registered in the evidence chain. When the buffer period has expired, the event enters the replay channel and the historical windows are corrected by sorting them according to window order and idempotency key. If the corresponding window has been audited and locked, the event is transferred to the isolation partition and a review task is generated without rewriting the original fixed record. The isolation partition is an audit storage area that is only accessible for auditing and review. It does not participate in downstream routine retrieval and window progression. Any write must be accompanied by the evidence chain hash and the cause must be recorded. Audit locking means that after the window event is fixed and written to the evidence chain hash, the storage area enters a read-only state. Historical corrections are only implemented through the replay channel in a parallel recording manner, and the original fixed record is not rewritten.

[0066] To enhance robustness, fault registration rules are established and assigned numbers, covering three scenarios: timing deviation exceeding limits, out-of-order buffer overflow, and idempotent key conflicts. When timing deviations continuously exceed tolerance, the timing source is downgraded and realigned, and the deviation and processing time are recorded. When a buffer overflow occurs, rate limiting and suspension of processing are implemented while maintaining the idempotent key sequence. When an idempotent key conflict is detected, a new key is formed by appending a sequence number salt to the original key value, and the conflict mapping relationship is written into the evidence chain. The old key remains read-only for retrieval. The system must not bypass the waterline and idempotent key constraints for writing. Any unauthorized requests to modify the ledger or evidence chain are rejected at the policy layer and trigger an audit alarm.

[0067] During the operational phase, arrival order consistency rate, upper limit of time deviation, and duplicate entry rate are used as routine indicators. The upper limit of time deviation is calculated according to a unified statistical standard, preferably the 95th percentile of the absolute deviation of arrival time. If necessary, the maximum value is used for verification during monthly audits. The alarm handling time limit can be set to complete the creation and confirmation of isolation and review tasks within a few minutes after the alarm is generated; preferably, it can be set to five minutes. The operational phase alarm threshold for duplicate entry rate can be set to 0.01%. When the threshold is exceeded, the relevant idempotent key is automatically written to the isolation partition and a review task is generated. During the deployment phase, the sample size and observation period covering different time periods and equipment types are used as the verification baseline. Preferably, the water level advancement step size can be set to one to five seconds, the out-of-order buffer time can be set to thirty to three hundred seconds, the end-to-end latency upper limit can be set to one hundred milliseconds, and the number of retries can be set to three. The arrival order consistency rate is preferably not less than 99%, and the upper limit of time deviation is preferably not more than one second. The freshness and consistency thresholds can be set to use different standards for peak and off-peak periods to adapt to rhythm changes.

[0068] Scenarios with additional time synchronization sources can be configured to use multi-anchor time bases instead of dual-anchor time bases, only expanding the list of time synchronization sources and alignment rules without changing the idempotent key structure and waterline strategy; alternatively, it can be configured to use hierarchical storage to distinguish between hot and cold data, maintaining append-only and evidence chain solidification unchanged; the communication mode can be configured with the local bus as the main channel and the message channel as the redundant channel, uniformly executing idempotent key deduplication and sequence locking rules; cross-window batch retransmission strictly follows the window order and idempotent key sorting for playback, prohibiting writing across the current advancement window to avoid disturbing the advancement order; the tolerance of the time synchronization alignment stamp can be set to an upper limit, triggering degradation and recording the recovery time when multiple consecutive time synchronization alignment stamps exceed the tolerance.

[0069] S2. Construct a key indicator caliber map and compile it into reward bytecode, including time windows, latency compensation, and weight fingerprints. Set a drift threshold, trigger caliber switching, and freeze replay. The specific implementation is as follows:

[0070] To stabilize the reward definitions for key indicators, in a field with multi-source measurements and a unified management ledger, a caliber chart is first compiled based on the indicator names, units of measurement, aggregation rhythms, allowable tolerances, and threshold boundaries recorded in the ledger. The caliber chart is a standardized set of values, unit conversions, aggregation cycles, threshold settings, weight allocations, and interdependencies for each key indicator, and it is implemented through version locking and record management. After unit normalization, rhythm alignment, and missing measurement completion, the caliber chart is compiled into reward bytecode. The reward bytecode is a reward description that can be directly called by the decision-making process, containing three elements: time window, delay compensation, and weight fingerprint. The time window is the boundary for performing aggregation and settlement within a fixed period; the delay compensation is the rule for carrying forward and reconciling late measurements; and the weight fingerprint is a fingerprint code generated from the weight vectors of multiple indicators, used to identify the reward composition.

[0071] The start and end of the time window are determined by a dual-anchor time base step. The dual-anchor time base is a unified time reference formed by both device time synchronization and communication time synchronization, used to determine the start and end of the time window and the source of the timestamp in the evidence chain. For scenarios involving cross-time zones and daylight saving time, the system-fixed time zone offset is used for timing, and this offset value is recorded in the evidence chain. Unit normalization follows a fixed decimal precision and rounding rules, which can be set to four decimal places and rounding to the nearest whole number. The rounding rules are consistent for positive and negative values ​​and boundary cases. When a value is exactly at the rounding boundary, it is rounded to an even number, and the rule version is recorded in the evidence chain. Records that exceed the allowable tolerance are marked as invalid and the original value is retained for auditing.

[0072] Reward bytecode is written to a read-only area and assigned a unique caliber version and effective time. All writes are based on idempotent keys, which are formed by combining the caliber version and effective time. Repeated arrivals are only recorded once according to the idempotent strategy, first-come, first-served, and later arrivals are not overwritten, only added to the change order. To maintain learning stability when the caliber changes, a drift threshold and trigger count are set, and the similarity and stability changes of weight fingerprints within adjacent time windows are continuously monitored. Stability is a comprehensive measure of the fluctuation amplitude and rate of change of indicators within a specified time window, and caliber consistency is the degree of consistency between the collected records and the caliber map field definition. Both are used as quality control calibers and are calculated in a rolling manner according to the time window rhythm, with a calculation frequency no less than the time window resolution.

[0073] The baseline fluctuation range can be determined by calculating quantile bands using historical sequences of the same caliber from the past seven to thirty days, taking the median and the difference between the upper and lower quantiles to form the range, and recording the value interval and sample size in the evidence chain. When the weighted fingerprint similarity is below the threshold and a stability mutation occurs in adjacent time windows to the set number, a caliber switch event is immediately issued and the corresponding replay window is frozen. The frozen replay window is a set of windows that have not been consumed by subsequent stages and allow version-by-version replay verification; after freezing, only read-only access is allowed. After the new version passes the stability verification for two consecutive observation periods, it is unfrozen in chronological order, following an idempotent key order, without adding, deleting, or skipping. The observation period is a continuous evaluation period after the caliber switch, which can be set to half a day to three days.

[0074] To control space usage, the total capacity and single-window entry limit can be set for frozen replay windows. When the limit is exceeded, the windows are unfrozen in segments according to time or retained in a rolling manner, without changing the order of the fixed windows. The fields are uniformly defined as version, time window, delay compensation, weight fingerprint, and freeze flag, and are distributed through the internal network configuration channel. The subscription mechanism adopts push as the main method and pull by version number as a supplement. The end-to-end latency limit for change notifications can be set to one to five minutes, and the percentile value of the actual time spent is recorded in the receipt. The subscriber must complete the receipt confirmation. If the confirmation is not completed within the time limit, an alarm will be triggered and the rollback path will be entered.

[0075] The read-only area implements concurrent write protection, employing a single-master sequential commit and version number comparison commit strategy to prevent concurrent write conflicts. When a comparison fails, an idempotent key is used for backoff retries until a commit is achieved or a rollback is triggered. To meet time and resource constraints, the end-to-end latency of the compilation chain is controlled within the upper limit allowed by the decision chain. A sharding parallelism and backoff retries strategy is used to manage concurrency and the number of retries. Backoff retries can be set to an incremental waiting limit, and the number of retries can be set to three to five. If the limit is exceeded, a rollback to the previous version is initiated, and the change order and hash are written to the evidence chain.

[0076] The evidence chain uses irreversible hash signatures, and the timestamps are derived from dual-anchor time bases. The evidence chain and the read-only area have at least two copies, which are stored across data centers. The consistency of the copies is achieved by submitting in master-slave order and recording the submission sequence number. Publishers, reviewers, and subscribers have hierarchical permissions. Changes to the version must be reviewed by two people before they can take effect. Publishers and reviewers belong to different role groups. Any cross-approval within the same group is invalid and written with an error number. The review record is also included in the evidence chain.

[0077] During predefined special operating periods, such as major holidays, the drift threshold can be set to a more conservative value or changed to require manual confirmation before triggering a change in reporting standards, with the relevant decisions and reasons solidified in the chain of evidence. If a rollback occurs, the rollback status can only be lifted after verifying that both the consistency and stability of reporting standards meet the thresholds within two consecutive observation periods. The verification of reporting standards includes consistency, stability, and the receipt rate during the observation period. The minimum receipt rate can be set at no less than 99%. If it falls below the threshold, a rollback is triggered and a new observation period begins. Preferably, during the observation period after the reporting standard switch, the consistency of reporting standards remains above the predetermined threshold and the stability returns to the baseline fluctuation range.

[0078] The fault numbering system covers situations such as missing version specifications, failed weighted fingerprint verification, conflicting frozen states, read-only zone write rejection, and notification timeout without response. The fault number format is a fixed three-segment combination (step code - fault code - serial number), with a fixed character set and length. Allocation ranges are registered in the ledger to avoid conflicts, facilitating automatic parsing and retrieval. Simultaneously, the associated occurrence scenario, field snapshot, and retry count are solidified into the evidence chain. Time-related fields are solidified in the format "year-month-day hour:minute:second plus time zone offset," prohibiting the use of ambiguous dates or relative descriptions. The minimum retention period for records in the read-only zone and frozen playback window can be set to no less than one year; upon expiration, records are processed according to the strategy of auditing first and then archiving.

[0079] In multi-tenant scenarios, the idempotent key prefix includes a tenant identifier, isolating different tenant versions of the evidence chain and prohibiting cross-tenant referencing. Preferably, the weighted fingerprint similarity threshold can be set to 0.97, the time window can be set to hourly to daily, and the trigger count can be set to two consecutive times; the consistency of the statements is preferably not less than 98%.

[0080] To take into account the measurement sensitivity of different sites, it can be set to use a multi-level weighted fingerprint hierarchical comparison. Without changing the composition of the reward bytecode field and the storage method of the read-only area, a more granular weight hierarchy is used to measure segment similarity. The drift threshold and trigger number are still issued according to the above criteria for switching and freezing instructions.

[0081] S3. Establish a reward and loan ledger, register debt instruments, construct forward and backward traces, settle rewards according to reward bytecode in the delay window, and weight samples according to quality quadruples. The specific implementation is as follows:

[0082] To establish traceable decision evidence in situations where reward delays exist, based on a fixed unified time-based event stream and consistent reward bytecode, actions are associated with arrival states one-to-one using idempotent keys to form a reward debit and credit ledger. The idempotent key is a key-value combination that uniquely identifies events within a window. It is calculated in a fixed order by the device identifier, time anchor, window order, template version, and feature signature, and is kept non-repeatable. The action number is a single-value number for an action instance under the same time base. An action instance is a single action record generated by the policy at a given time under the unified time base and syntactically verified. The arrival state number is the number of the first controlled state reached after the action.

[0083] The reward and loan ledger is a continuous record of outstanding and settled rewards. Debt notes are pending entries registered when an action occurs, including idempotent keys, action numbers, arrival status numbers, caliber versions, and creation timestamps. The forward trace is the association chain from the action along the time base to the arrival status, and the backward trace is the association chain tracing back from the settlement point to the action during reward settlement. The two close the reconciliation link. The delay window is the time span that allows rewards to be settled within the delay. The reward bytecode is an executable reward description body compiled based on the caliber map, including time windows, delay compensation, and weight fingerprints. The quality quadruple is completeness, freshness, consistency, and credibility, and is used to determine sample weights and ledger inclusion eligibility.

[0084] On-site, field alignment, missing test completion, and out-of-bounds value adjudication are first completed based on a unified time base and quality label. Then, debt instruments are registered and forward traces are generated when each action is completed. When the time window defined by the reward bytecode enters the settlement state and the delay window expires, settlement is performed in the ledger according to the corresponding caliber version, and weighting is completed by mapping the quality quadruple to the weight coefficient. The mapping rule adopts a hierarchical table and is locked with the caliber version. Preferably, completeness, freshness, consistency, and credibility are mapped to discrete coefficients according to three levels of quantiles. The hierarchical table is stored in the read-only area and the version hash is registered in the evidence chain.

[0085] All timestamps use millisecond-level resolution consistent with the time anchor and are recorded based on Coordinated Universal Time (UTC). When presented, they are rendered in the local time zone without changing the storage caliber. The reconciliation list is a summary record used for auditing and review, which includes idempotent keys, action numbers, arrival status numbers, settlement timestamps, caliber versions, and weight coefficients. It is written to the append-only partition of the ledger area in an append-only manner. At the same time, a dual index is created based on idempotent keys and ledger sequences for use by the policy evaluation loop. The reconciliation list is batch-signed and hashed and stored in the audit storage. The retention period can be set to two years or more. Upon expiration, it is archived and the batch index is retained for playback.

[0086] The ledger-specific area is an independent logical area decoupled from training and inference. The append-only partition is a sequential write area that prohibits modification and deletion. The audit storage is a read-only area with immutable verification and sequential index. The audit index is a set of evidence organized by keys in this read-only area, including batch signatures, hashes, threshold parameters, and time anchors, used for review and traceability. Upstream and downstream connections are made using idempotent keys and ledger sequences. Communication uses local reliable channels or controlled message channels. The order is guaranteed by window advancement and sequence number barriers. Idempotency is controlled by idempotent keys to remove duplicates and prohibit duplicate settlement. When there is an idempotent key conflict, the first-come-first-served principle is used, and only the quality quadruple and audit trace are updated. Newly arrived records are not duplicated and the conflict factor and time stamp are registered.

[0087] On the resource side, a two-level strategy of parallel partitioning and sequential merging can be set. The partition key is a prefix hash of an idempotent key, and the sort key is an ordered pair of ledger sequence and time anchor. In the parallel registration stage, the data is partitioned according to the partition key, and in the merging stage, it is stably stored according to the sort key. To ensure consistency, a retry sequence and a maximum number of attempts are set. Retry follows a fixed backoff curve. Preferably, the maximum number of attempts can be set to three, and the retry backoff curve can be set to an exponential upper limit capping strategy. Preferably, the interval between two adjacent retry is not less than twice the previous interval and does not exceed the predetermined upper limit. If the upper limit is exceeded, a rollback is triggered, and a rollback factor and final disposal are registered in the evidence chain. The rollback factor is a combination of the reason code for triggering the rollback and the context summary, which is used to record the basis for the rollback decision and its reproduction.

[0088] On the time side, an end-to-end delay limit is set for ledger registration, settlement, and list generation. During the caliber switch, all outstanding debts and bills that have not been settled before the switch point are frozen. The unfreezing condition is the completion and release of the switch event between the old and new versions. The frozen bills are settled according to their original caliber version. On the version side, the reward bytecode, ledger structure, and list template are version locked. Any changes will generate a chain of evidence records with signatures and hashes and be stored in the audit storage and can be queried.

[0089] Security and compliance boundary requirements stipulate that debt instruments with restricted actions can only be registered within feasible domains. A feasible domain is a set of actions that meet the compliance list, service level thresholds, and physical boundaries. Out-of-bounds proposals are not recorded and the adjudication factor is recorded. Ledger access is controlled by an authorized list and transmitted with session keys for encryption. Any unauthorized access is recorded in the audit index with the subject identifier and time anchor. The verification criteria include settlement coverage, reconciliation consistency rate, debt clearance rate, and ledger consistency verification. Coverage rate indicates the percentage of items that have been settled after the delay window closes. Reconciliation consistency rate indicates the key-by-key matching rate between ledger items and event-fixed records. Debt clearance rate indicates the percentage of overdue unsettled items that have been cleared. Ledger consistency verification is used to compare the dual indexes and the actual storage status.

[0090] Fault management uses a coding system of module number plus three-digit serial number to record reconciliation failures, settlement timeouts, duplicate invoices, and unauthorized access events. The retention period is no less than two years and audit records are kept. The data lifecycle follows retention and archiving rules. Settled items enter the archiving area after the retention period expires. Before archiving, a list is generated and written into the evidence chain without affecting audit playback. Preferably, the delay window can be set to one hour to twenty-four hours, with a coverage rate expected to be no less than 98%, a reconciliation consistency rate expected to be no less than 99%, and an outstanding debt clearing rate expected to reach zero within one day after the window closes. The end-to-end latency limit for ledger registration and list generation within a single window is no more than one-tenth of the predetermined decision-making link time limit.

[0091] When a version switch occurs during peak business periods, the debt notes corresponding to the old version are frozen until the switch is completed before being settled. Notes under the new version are registered with new weighted fingerprints and the first batch settlement is completed within 24 hours. Alternatively, a single-layer ledger can be replaced with a hierarchical ledger, maintaining notes and lists separately in different business domains, while keeping the idempotent key composition, ledger sequence semantics, and list fields unchanged, thus not changing the technical essence and causal chain.

[0092] S4, compliance rules and service level thresholds are compiled into action syntax. Syntax checks, interval pruning, mutual exclusion resolution, and feasible region projection are performed on the policy output. A barrier function and budget Lagrange update are introduced, and multipliers converge according to the cooling curve. The specific implementation is as follows:

[0093] In a field with unified time base and idempotent key management, compliance lists, service level thresholds, and physical boundaries are compiled into action syntax. Action syntax is a production structure for the action space of policies, providing three types of constraints: templates, continuous intervals, and mutually exclusive sets. Templates specify action fields, value ranges, units, precision, tolerances, and triggering rhythms. Continuous intervals specify the upper and lower bounds and closure methods of each continuous control variable. Mutually exclusive sets specify discrete option groups that allow only one of them to be effective at any given time. The production structure is a finite set description of action fields and their value relationships, including field names, value ranges, dependency order, and mutually exclusive constraints, without involving context-dependent rules.

[0094] After the strategy generates the initial action, a syntax check is performed first, verifying the completeness of fields, unit consistency, rhythm alignment, and interlocking constraints item by item. For consecutive components that exceed the boundaries, interval pruning is implemented, pushing the boundary points back within the predetermined upper and lower bounds. For multiple proposals belonging to mutually exclusive sets, mutual exclusion resolution is implemented, determining a unique item according to preset priorities. When items with the same priority appear, a unique item is given according to the stable sorting rule of field names to ensure reproducibility. The stable sorting rule can be set to compare in ascending order based on the unified encoding order of field names, using a unified character set for all encodings, and adding a sequence number before comparison when encountering fields with the same name. Subsequently, feasible domain projection is implemented. Under the condition of simultaneously satisfying the compliance list, service level threshold, and physical boundaries, the pruned action is mapped to the nearest neighbor within the feasible set, and an adjudication record is generated. The nearest neighbor refers to the closest feasible point obtained under the normalized scale given by the template and the weighted distance metric locked by the version. This distance metric and weight vector are locked along with the action syntax version. The feasible set refers to the set of actions that simultaneously satisfy the compliance list, service level threshold, and physical boundaries, and is locked along with the action syntax version.

[0095] To suppress the risk of exceeding limits and training oscillations, boundary term constraints are set and the constraint strength is adjusted by using a budget multiplier constraint update method. The budget multiplier converges with the cooling curve, which can be set to decrease in segments, with each segment's step size not exceeding 70% of the previous segment. When the window mean of the budget multiplier's change amplitude is not higher than one percent, the heat preservation stage is entered, with the step size remaining unchanged. The statistical window for the window mean can be set to three to five decision windows, with three as the default.

[0096] The adjudication results and constraint records are written to the adjudication area, which is an append-only structured storage partition. The fields include action syntax version, business domain identifier, fragment sequence number (a monotonically increasing number within the same business domain, used to resolve concurrency within the same second, compared in ascending order, and prohibiting wraparound), interval pruning details, mutual exclusion resolution details, feasible domain projection results, budget value, multiplier trajectory, time anchor (referring to the window time identifier after alignment with the double anchor time base), idempotent key, adjudication timestamp, and signature hash (bound to the version number). Within the same business domain and the same fragment, the data is sorted by the time anchor and sequence number double key to maintain order consistency. Downstream gating retrieves adjudication records according to the action syntax version and performs concurrency threshold determination; the concurrency threshold is an admission determination that is not lower than the baseline revenue threshold and the constraint default prediction (referring to the upper bound of the gating's estimate of the default rate of the next decision window, calculated based on recent adjudication records and constraint trigger trajectories) is not higher than the budget threshold; the baseline revenue threshold and the budget threshold are derived from the acceptance baseline of the previous period, preferably the historical median plus a conservative lower bound; the conservative lower bound can be set as the historical lower quartile of the indicator in the same period or the value after reducing the confidence lower bound, and the selected caliber is locked according to the gating and audit template version. The communication link uses a low-latency channel within the same city's intranet to directly reach the execution plane. The end-to-end latency limit is the maximum allowable latency from the formation of the policy action to its execution, preferably not exceeding one hundred milliseconds. When the end-to-end latency limit is reached, the baseline action (referring to the action generated by the currently effective baseline policy under the same action syntax) is directly rolled back and recorded. The rollback record includes at least the baseline policy version, rollback factor, trigger criterion hash, time anchor, and rollback timestamp. These fields are locked with the audit template version and written into the evidence chain. Three consecutive timeouts within the same shard trigger rate limiting, preferably for thirty seconds, and the cooling intensity is increased accordingly (the step size limit ratio is reduced).

[0097] To handle peak traffic and cross-domain isolation, concurrency can be set to two to sixteen channels. For occasionally failing units, partial retries can be performed while maintaining sequential consistency, with the number of retries set to one to three. Field performance is evaluated using the constraint default rate and convergence stability. The constraint default rate is the percentage of actions that still exceed the limits after adjudication. Convergence stability is the joint stability index of the budget multiplier change amplitude and the action amplitude fluctuation. Names, units, rhythms, and tolerances are derived from field records and managed uniformly through templates. All fields undergo unit normalization, rhythm alignment, and missing measurement completion before adjudication. The allowed phase deviation for rhythm alignment is no more than one-tenth of a single acquisition cycle. Missing measurement completion follows a strategy of prioritizing playback completion, followed by amplitude limiting interpolation, and finally discarding. The strategy selection is locked with the template version.

[0098] Idempotency, ordering, and deduplication strategies use idempotent keys to control unique writes, watermarks to advance locking order, and an idempotent key conflict table to register duplicate arrivals and perform only idempotent updates. Out-of-bounds proposals are defined as one of three events: touching physical boundary hard limits, touching service level thresholds, or triggering a blacklist (a set of actions explicitly prohibited in the compliance list). Once triggered, the out-of-bounds factor is directly pruned and registered before feasible domain projection. Fault numbers use a fixed format of a four-digit primary key plus a two-digit subkey. The primary key identifies the stage, and the subkey identifies the reason; for example, 0101 indicates a missing field in syntax checking, and 0202 indicates that feasible domain projection out-of-bounds failed pruning. Fault records include a time anchor, idempotent key, failed stage, and number of retries.

[0099] The compliance rules, action syntax, cooling curve, and budget strategy are implemented with version locking. Any change generates a change order, signature, and hash, which is written into the evidence chain. The evidence chain is an immutable set of records with signature hashes, covering the critical path from syntax checking, interval pruning, mutual exclusion resolution, feasible region projection to gating decision. The retention period for evidence chain records can be set from twelve to thirty-six months, with a default of twenty-four months. Upon expiration, the records are archived for read-only access. While maintaining the above essential features, the communication mechanism can switch between service calls and message queues, the storage medium can switch between columnar storage and log-type storage, and the sharding strategy can switch between business domain sharding and time window sharding. All of these are considered equivalent replacements and do not change the technical essence or the scope of protection of the claims.

[0100] S5. Set up an out-of-bounds detector, determine out-of-bounds samples based on feature covariance radius and kernel distance, perform confidence reduction and target network mildening on out-of-bounds samples, and combine this with order-preserving truncation. Playback only accepts samples that meet the quality threshold. The specific implementation is as follows:

[0101] Given the established dual-anchor time base and idempotent bond, an out-of-distribution detector is set up before the training batch is formed to judge candidate samples in order to suppress the estimation bias caused by out-of-distribution samples. The out-of-distribution detector refers to a mechanism that measures the degree of sample deviation by jointly measuring the feature covariance range and kernel distance in a unified feature space. The feature covariance range is an ellipsoidal range formed by the feature statistics of the stable subset. The stable subset refers to the set of samples that meet the quality quadruple threshold within the sliding window under the previous version caliber. The kernel distance is the distance metric after kernel mapping. The two are combined by weight to form the out-of-bounds degree. The weighting caliber can be set to a closed interval of 4:6 to 6:4. The default is to take half of each and is reviewed and adjusted quarterly by the out-of-bounds interception rate and the false interception rate. The false interception rate refers to the ratio of stable subset samples judged as out of bounds by the out-of-distribution detector and triggering confidence reduction. The statistics are rolled by the observation window.

[0102] The observation window is used for the time range of statistics and adjudication, which can be set from 15 minutes to 2 hours, with a default of 30 minutes; the sampling period can be set to be consistent with the step size of the observation window, preferably one to five seconds, which is used as the time reference for majority decisions and batch merging; the end-to-end decision time limit can be set to within 100 milliseconds. When the time consumption of the inference path exceeds 80% of this upper limit, the off-distribution decision, index writing and evidence chain recording become asynchronous and do not block the inference path. The inference path refers to the real-time link from policy invocation to action adjudication.

[0103] When the out-of-bounds condition is met, confidence reduction is applied to the relevant estimates to decrease the influence of the sample on the current estimate. Simultaneously, the target parameter replica is smoothed to suppress drastic oscillations. The target parameter replica smoothing level can be set to three levels. Preferably, the lowest level suppression ratio is no higher than 5%, the medium level no higher than 10%, and the high level no higher than 15%. The default is medium level. To prevent direction reversal and overestimation, monotonicity truncation is used to limit the amplitude and direction of each update. Before entering the replay buffer, samples must pass a replay quality threshold, which is given by a quality quadruple. The quality quadruple consists of completeness, freshness, consistency, and reliability. Preferably, completeness is no less than 98%, consistency is no less than 95%, and reliability is no less than 90%. Samples that do not meet these requirements are marked as read-only and retained for auditing, and are not included in training.

[0104] The replay buffer is an experience replay area used to store sample sets that have passed the quality threshold. It employs an append-only write and idempotent key sequential read mechanism, serving as a stable sample source for training batches. The sample index area uses an idempotent key as the primary key and appends only, recording the bounds, confidence reduction flag, target parameter copy smoothing level, and monotonicity truncation flag, and associating them with the batch sequence and caliber version. Upstream, index changes are pushed via the local bus or message channel, and downstream training batches are read sequentially according to the watermark progression and batch sequence locking. Duplicate arrivals are merged using the idempotent key and are not counted again in the update.

[0105] The concurrency and timing of training batches are controlled by sharding scheduling and time windows. The triggering condition can be set to the window expiring or the sample count reaching a threshold. The sample count threshold can be set to no less than 1,000 and no more than 100,000 samples per batch, with a default of 10,000 samples. The sharding granularity and maximum concurrency of sharding scheduling can be set to be equally divided according to idempotent key hashing, with the maximum concurrency not exceeding 80% of the available computing resources, and the remainder used for inference paths and audit disk write-to-disk.

[0106] When batch stability decreases or the time exceeds the limit, the process rolls back to the most recent stable batch and records the evidence chain. Batch stability is a dual indicator consisting of the estimated high percentile fluctuation and batch time. Preferably, the 95th percentile fluctuation is no higher than 20% of the baseline and the batch time is no higher than the set upper limit. The upper limit of batch time can be set to the 95th percentile of the sample time in the observation window plus a safety margin. The default safety margin is 10%. After the rollback is triggered, the process rolls back to the most recent stable batch first. Retry uses exponential backoff, with an initial backoff of one second and an upper limit of thirty seconds. Retrying will not exceed three times, and all retrying will be written into the evidence chain. The evaluation criteria include out-of-bounds interception rate, estimated stability, and playback quality ratio. The out-of-bounds interception rate refers to the proportion of samples that are identified and effectively downweighted within the observation window. The estimated stability refers to the estimated fluctuation amplitude measured in quantiles. The playback quality ratio refers to the proportion of samples that meet the quality threshold in the total playback volume. Preferably, the out-of-bounds judgment is triggered by the high quantile of the Mahalanobis radius superimposed with the kernel distance threshold. The high quantile is set to 99% by default. When it comes to estimated stability, the 95th quantile is used as the preferred criterion for fluctuation evaluation. In representative cases, after enabling this mechanism, the estimated high quantile fluctuation is significantly reduced compared to when it is not enabled, and the playback quality ratio remains above the set lower limit.

[0107] When adjacent batches have inconsistent out-of-bounds judgments, a merging condition is applied. The merging condition requires at least two batches out of three consecutive batches to give consistent judgments within a sampling period. If this condition is met, the majority judgment prevails. If inconsistencies still exist, the more conservative side is retained, and a rollback process is initiated. The evidence chain refers to a read-only audit storage that records key decisions, version signatures, and hashes. It employs a two-stage disk write strategy: first, it writes to the memory log, then it writes to disk in batches. The batch period can be set to ten to sixty seconds. In case of an anomaly, it immediately synchronizes the disk write and locks the current batch sequence number. All judgment rules, weight settings, smoothing strategies, and thresholds are version-locked. Version changes generate change orders and are written to the evidence chain.

[0108] Fault numbers use a three-letter followed by a three-digit encoding method. Preferably, OOD 001 indicates an out-of-bounds judgment mismatch, OOD 002 indicates insufficient playback quality, and OOD 003 indicates a smoothing level exceeding the limit. The number is indexed by time anchor, batch sequence, idempotent key, and caliber version and written into the evidence chain. The safety and compliance boundaries are carried out by action syntax and service level thresholds. Any out-of-bounds proposal, even if it meets the playback quality threshold, must not enter training or execution. This step forward connects to the risk sources formed by action syntax adjudication and backward provides the gating step with estimated trajectories and uncertainty signals layered by label.

[0109] The gating process refers to the online stage where gray-scale scaling and rollback decisions are made based on multiple lower bounds and constraint budgets. The decision results and scaling trajectories are written into the audit index and bound to the caliber version. To adapt to different scenarios, a conservative interval radius can be used instead of kernel distance assessment, but the following essential features remain unchanged: out-of-distribution detector, out-of-bounds synthesis, confidence reduction, target parameter copy smoothing, monotonicity truncation, playback quality threshold, and sample index field. Interface fields, version signatures, and evidence chain traceability also remain unchanged. The above configuration is implemented without altering the end-to-end decision-making timeline and concurrency strategy. Idempotency, ordering, and deduplication strategies are executed with dual constraints of idempotency keys and water level lines to ensure stable, traceable, and verifiable estimation results under non-stationary and delayed feedback conditions, and to maintain consistent communication and timing caliber with upstream and downstream stages.

[0110] S6. Calculate the lower bound of importance sampling, robustness, and empirical risk, set a conjunctive threshold, advance the flow based on quantiles when the threshold is reached, and back off if the boundary is exceeded. Generate an audit index to solidify the ruling and the flow trajectory. The specific implementation is as follows:

[0111] To quantify online access and enable traceable review, the gating link completes the calculation of conservative boundaries for three types of returns, the determination of access to consolidation, and the gray-scale quantification within a fixed hourly observation window. The sliding step size can be set to five to fifteen minutes. If minute-level rapid review is required, a separate rapid review window can be set. The rapid review window is only used to trigger early warnings and enhance observation. It does not generate consolidation threshold determinations or volume increase actions, does not write to the adjudication record, and only registers early warning traces in the audit index.

[0112] The three types of lower bounds include the sampling weight truncation lower bound, the robust lower bound, and the empirical risk lower bound. The statistical definitions, quality thresholds, and window ranges of the three types of lower bounds are consistent. The quality thresholds follow the definition of the quality quadruple, requiring that completeness, freshness, consistency, and credibility are not lower than their respective thresholds, and the four thresholds and their versions are registered in the audit index. The confluence threshold is defined as the three types of lower bounds being simultaneously not lower than the set thresholds and the constraint default prediction not exceeding the budget threshold. The determination order is fixed as first checking the constraints and then comparing the lower bounds. The budget threshold refers to the permissible upper limit of the constraint default rate under the same time anchor and observation window. It is derived from a fixed value of historical regression over the past two to four weeks, and the predictor version and threshold version are registered in the evidence chain. The budget default predictor implements version locking and records the version number and effective range in the audit index. When the confluence threshold is not met, the baseline strategy is maintained and the reason for rejection is recorded.

[0113] When the confluence threshold is met, gray-scale quantization is performed according to the segmented sequence. Preferably, the quantiles are set to 30% for the low segment, 60% for the middle segment, and 100% for the high segment. The maximum increase in volume within a segment can be set to 10% to 20%, and the freeze duration within a segment can be set to 5 to 15 minutes for stabilization and verification. If any constraint exceeds the limit, the strategy is rolled back to the baseline strategy and the rollback factor is recorded. The rollback factor must include at least the constraint name, the extent of the rollback, the judgment time anchor, the statistical version, and the associated idempotent key. The restart condition after rollback is that two consecutive windows meet the criteria, where two consecutive windows refer to two adjacent main observation windows. To ensure the consistency of threshold determination, the baseline return threshold is the threshold for calculating the baseline strategy return using a fixed statistical caliber under the same time anchor, the same observation window, and the same statistical version. Preferably, the quantile method or the median method is used, and the statistical caliber version used is recorded in the audit index.

[0114] Gated decision-making uses an independent resource pool with higher priority than statistical links. The end-to-end latency limit can be set to 100 milliseconds, the number of concurrent decision-making channels is no less than ten, and the depth of the pending decision queue is no less than 1,000. Decision notifications are distributed through either the local high-speed channel or the intranet message channel. Messages have transactional semantics, and the delivery strategy is at least one delivery with idempotent key deduplication on the receiving side. Message identifiers correspond one-to-one with idempotent keys, and the receiving side uses the idempotent key as the unique deduplication key. Timeouts or retries do not change the idempotent key value, and the maximum number of retries is three. If the threshold is exceeded, it automatically degrades to the baseline strategy and registers a fault code. The write order is locked by time anchors and segmented sequences. All writes use idempotent key control for unique decision-making. Parallel arrivals with the same idempotent key are fixed on a first-come, first-served basis, with other entries marked as duplicates and discarded. Cross-segment write-back is prohibited.

[0115] The audit index is used for review and compliance verification, and at least includes concurrency threshold parameters, three types of lower bound details, window start and end and sliding step size, statistical caliber version, quality threshold, gray-scale rollout plan, actual volume curve, rollback factor list, adjudication signature hash, hash algorithm version, audit template version, access control level and time anchor; the access control level is divided into three levels: read-only, audit, and management. Query and change permissions are restricted by the role table and evidence chain signature verification, respectively. The role table name and version number are written into the audit index; the audit index and the evidence chain correspond one-to-one. The gating rules, caliber version, audit template and predictor version are all version locked. Each change generates a change order and signature hash, which are concatenated to the evidence chain.

[0116] The evaluation criteria include the success rate of volume expansion, rollback trigger rate, consistency between the lower bound of revenue deviation and the online assessment deviation, constraint default rate, and end-to-end latency stability. The sample size is measured by the effective samples within the observation window. Preferably, progress can only proceed when all three lower bounds are simultaneously higher than the baseline revenue threshold by approximately 1.5% and the default prediction is no higher than 0.2%, and the absolute difference between the lower bound of revenue deviation and the online assessment deviation is no higher than 1%. A fault numbering system is set for the gating link: gating calculation timeout is recorded as code E601, rollback execution failure is recorded as code E602, audit solidification failure is recorded as code E603, and resource or latency exceeding limits and degrading to the baseline strategy is recorded as code E610. When a fault occurs, the time anchor, link, field, and number of retries are retained, and the evaluation is carried out again in the next observation window.

[0117] Auditing and storage adopt an append-only strategy, with a maximum retention period of 90 days. Once the cold storage migration conditions are met, the system will move to cold storage and retain the index. The cold storage migration conditions can be set to migrate if there are no queries or cases are closed within 90 days, and the migration timestamp will be recorded. The security boundary is pruned before scaling up by action syntax and service level thresholds. Any out-of-bounds proposals are rejected and registered before being projected into the feasible domain. To maintain the technical substance while improving engineering adaptability, the specific calculation of the three types of lower bounds can be replaced by an equivalent conservative estimate of the interval. However, the parallel status of the three types of lower bounds, the conjunctive decision structure, and the gray-scale advancement mechanism remain unchanged.

[0118] All calculations involved in the embodiments are dimensionless numerical calculations, and the preset parameters and thresholds in the calculations are set by those skilled in the art according to the actual situation.

[0119] It should be noted that this invention can be deployed on the device itself to realize embedded applications, or it can run on a PC or other terminal with a user interface, thereby meeting various hardware environments and usage requirements.

[0120] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wireless or wired transmission; wired transmission methods include optical fiber, twisted pair, coaxial cable, etc.; wireless transmission includes infrared, microwave, etc. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center containing one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0121] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and modules described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0122] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0123] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0124] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0125] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0126] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0127] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for constructing an intelligent decision-making cockpit based on reinforcement learning, characterized in that, include: S1. Establish a dual-anchor time base, set up a disordered buffer and water level line, generate idempotent keys according to equipment identification, time anchor, window order, template version, and feature signature, solidify events and label quality quadruples; S2. Construct a key indicator caliber map and compile it into reward bytecode, including time window, delay compensation and weight fingerprint, set a drift threshold, trigger caliber switching and freeze playback; S3. Establish a reward loan ledger, register debt notes, construct forward and backward traces, settle rewards according to reward bytecode in the delay window, and weight samples according to quality quadruples. S4, compliance rules and service level thresholds are compiled into action syntax, and the policy output is subjected to syntax verification, interval pruning, mutual exclusion resolution and feasible region projection. Barrier functions and budget Lagrange updates are introduced, and multipliers converge according to the cooling curve. S5. Set up an out-of-bounds detector, determine out-of-bounds based on feature covariance radius and kernel distance, perform confidence reduction and target network mildening on out-of-bounds samples, and combine with order preservation truncation. Playback only accepts samples that meet the quality threshold. S6. Calculate the lower bound of importance sampling, robustness, and empirical risk, set a conjunctive threshold, advance the flow according to quantiles when the threshold is reached, and back off when the constraint exceeds the limit. Generate an audit index to solidify the decision and the flow trajectory.

2. The method for constructing an intelligent decision-making cockpit based on reinforcement learning according to claim 1, characterized in that, S1 includes: Establish a dual-anchor time base under the locked ledger version, and register the time synchronization source, calibration cycle and tolerance; Set up a disordered buffer and proceed according to the water level line; Generate idempotent keys based on device identifier, time anchor, window order, template version, and signature. When the window coverage reaches the water level, the event is written to the event store in append-only mode using the idempotent key, the evidence chain hash is calculated, and the audit index is generated and registered. The quality quadruple is registered simultaneously, including completeness, freshness, consistency, and credibility; Playback of late events during the buffer period; playback after the buffer period; retransmission of events after the buffer period. Audited and locked records are transferred to the isolation zone and registered for review tasks, without rewriting the original fixed records.

3. The method for constructing an intelligent decision-making cockpit based on reinforcement learning according to claim 1, characterized in that, S2 include: Based on the ledger, a caliber map is generated and compiled into reward bytecode. The reward bytecode consists of a time window, latency compensation, and weight fingerprint. The start and end of the time window are determined by the dual-anchor time base. The reward bytecode is stored in a read-only area and version locked, and is uniquely controlled by an idempotent key consisting of a fixed combination of the caliber version and the effective time. When a version change occurs, a change order and signature hash are generated and written into the evidence chain; The read-only area adopts a single-master sequential commit and version number comparison strategy. If the commit fails, an idempotent key-based backoff retry is performed. If the retry fails, the version is rolled back to the previous effective version.

4. The method for constructing an intelligent decision-making cockpit based on reinforcement learning according to claim 3, characterized in that: Set the drift threshold and trigger count, continuously monitor the similarity and stability of weighted fingerprints within adjacent time windows, and issue a caliber switching event and freeze the corresponding replay window when the drift trigger condition is met; The playback window is read-only and maintains the idempotent key order; no new entries, deletions, or skipping are allowed. After the new version passes stability and consistency checks during the continuous observation period, it will be unfrozen in chronological order. Changes are distributed through the intranet configuration channel and confirmed by the subscriber. If confirmation is not completed, the system will enter the rollback path. The entire process of freezing and unfreezing is written into the chain of evidence and records the version of the statement, the effective time, and the freezing mark.

5. The method for constructing an intelligent decision-making cockpit based on reinforcement learning according to claim 1, characterized in that, S3 include: Establish a reward and loan ledger on a unified time-based event stream, register debt notes when strategy actions are generated, and uniquely associate actions with arrival states using idempotent keys; When the delay window expires, the reward is settled based on the reward bytecode, and the accounting is recorded according to the weight of the quality quadruple mapped by the hierarchical table; Write the reconciliation list to the ledger's dedicated area in an append-only manner and create an idempotent key index and a ledger sequence index; When an idempotent key conflict occurs, the first record to arrive is fixed, and the later record is not duplicated. The conflict factor is registered, the quality quadruple label is changed by adding an entry, and the evidence chain record is registered in the audit storage. Version locking is implemented for the reward bytecode and the tiered table, and change records are written to the audit storage.

6. The method for constructing an intelligent decision-making cockpit based on reinforcement learning according to claim 1, characterized in that, S4 include: Under dual-anchor time base and idempotent key constraints, the compliance list, service level thresholds and physical boundaries are compiled into action syntax; Output the data using a processing strategy that proceeds in the order of syntax checking, interval pruning, mutual exclusion resolution, and feasible region projection. Within a feasible set that simultaneously satisfies the compliance list, service level thresholds, and physical boundaries, nearest neighbors are determined based on a weighted distance metric locked by the action syntax version. The constraint strength is updated along the cooling curve using a budget multiplier. Write the decision record into the decision area and lock the order with time anchors and fragment numbers. Record the action syntax version, feasible region projection result, budget value, multiplier trajectory, time anchor, idempotent key and signature hash.

7. The method for constructing an intelligent decision-making cockpit based on reinforcement learning according to claim 1, characterized in that, S5 include: Set up an out-of-bounds detector and synthesize the feature covariance range and kernel distance in a unified feature space as the out-of-bounds degree; The covariance range is determined by a stable subset that meets the quality quadruple threshold and is based on the previous version's caliber. When the out-of-bounds degree reaches the out-of-bounds judgment, confidence reduction is applied to the sample, smoothing is applied to the target parameter copy, and monotonicity truncation is applied to the parameter update. Only samples that meet the playback quality threshold are allowed into the playback buffer; The sample index area records the bounds, confidence reduction flags, target parameter copy smoothing level, and monotonicity truncation flags using idempotent keys as the primary key, and writes them to the audit storage with version locking.

8. The method for constructing an intelligent decision-making cockpit based on reinforcement learning according to claim 1, characterized in that, S6 include: Within a fixed observation window, the sampling weight truncation lower bound, robust lower bound, and empirical risk lower bound are calculated. The statistical caliber, quality threshold, and window range of the three types of lower bounds are consistent. Set a concurrency threshold and perform admission determination in the order of first checking the constraint budget and then comparing the three types of lower bounds; If the concurrency threshold is not met, the baseline strategy is executed, and the rejection reason, time anchor, and threshold version are recorded in the audit index. The budget default predictor, statistical caliber, and baseline revenue threshold are version-locked, and the version identifier is recorded in the audit index.

9. The method for constructing an intelligent decision-making cockpit based on reinforcement learning according to claim 8, characterized in that: After the aforementioned admission determination is passed, the gray-scale phased advancement is implemented according to the segmented sequence, with an independent resource pool executing the decision and setting the end-to-end latency limit. The write order is locked by time anchors and segmented sequences, and the adjudication record is uniquely fixed by idempotent keys; If any constraint goes out of bounds, the strategy is reverted to the baseline and the revert factor is recorded. The audit index records the threshold for concatenation, the details of the three types of lower bounds, the start and end points of the window and the sliding step size, the quality threshold, the gray-scale rollout plan, the volume increase trajectory, the rollback factor, the signature hash and the version identifier.

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