Task assignment method for multi-role employment mode

Abstract

The invention discloses a task assignment method for a multi-role employment mode, and relates to the technical field of intelligent scheduling, and the method comprises the following steps: building a responsibility chain topological structure, extracting cross-role responsibility elements according to a task target, task input, task output, a task preposition constraint and a task postposition constraint, generating a responsibility vector, and carrying out the task assignment of the multi-role employment mode. And a verifiable responsibility map is constructed. According to the method, a verifiable task responsibility chain is constructed, and responsibility visualization, contract verifiability, semantic alignment and time sequence closed loop of the whole task disassembly and handover process are realized through responsibility graph modeling and contract fingerprint binding; the method combines consistency verification and shadow path calculation, dynamically identifies and repairs the risk of chain breakage, improves the scheduling stability and the task execution credibility, and solves the problem that the breakage of the chain of responsibility is difficult to identify and repairs in the prior art.

Description

Technical Field

[0001] This invention relates to the field of intelligent scheduling technology, specifically to a task assignment method for multi-role employment modes. Background Technology

[0002] "Task assignment for multi-role employment models" refers to a task scheduling mechanism within an organization or platform that intelligently assigns and dynamically adjusts tasks based on the abilities, responsibilities, contractual constraints, available time, and task matching of various employment roles (such as full-time employees, part-time workers, outsourced workers, temporary workers, and crowdsourced workers). This model breaks away from the fixed task assignment methods of traditional single-employment models, emphasizing flexible collaboration and role difference awareness. It typically achieves high efficiency, matching, and dynamic sustainability in task assignment by introducing role profile modeling, structured task requirements, role-task adaptation rules (such as priority, cost, and skill matching), and real-time feedback mechanisms. For example, in large manufacturing enterprises, the system can prioritize assigning tasks to highly skilled and currently available full-time workers based on their urgency; while for non-core, short-term tasks, it may prioritize scheduling crowdsourced workers or outsourced teams. This approach can significantly improve employment flexibility, task completion efficiency, and the organization's overall resource allocation capabilities.

[0003] The existing technology has the following shortcomings: In existing technologies, task assignment for multi-role employment models typically involves the system automatically identifying task units and splitting and assigning tasks based on role capabilities, availability of working hours, or collaboration strategies. Especially in dynamic collaborative scenarios, some continuous tasks that should originally be completed independently by a single role may be broken down into multiple sub-tasks by the system according to configuration rules and assigned to different roles. However, existing technologies generally lack mechanisms to verify the integrity of the responsibility chain within a task, particularly after tasks are split across roles, failing to dynamically verify the consistency of task boundaries, handover processes, and responsibility loops between roles. This deficiency is particularly prominent in multi-process sequential tasks. For example, in manufacturing scenarios, the lack of clear task chain connections and responsibility confirmation mechanisms in the collaborative work between front-line production operators and subsequent equipment maintenance and quality inspection personnel can easily lead to a disconnect in responsibility midway through the task.

[0004] More seriously, when faced with sudden task restructuring (such as temporary personnel replacement, task priority adjustment, or outsourcing), existing systems often fail to trigger the cross-responsibility chain re-verification process, resulting in hidden breaks in the task execution process going undetected in a timely manner. Once such breaks occur, they often manifest as abnormal behaviors such as distorted task status, misjudgment of roles, process interruption, and inability to trace results. Ultimately, this can lead to quality incidents, safety hazards, or large-scale rework, severely impacting the organization's labor efficiency and task execution reliability. The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide a task assignment method for multi-role employment models to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a task assignment method for multi-role employment models, comprising the following steps: Establish a responsibility chain topology, extract cross-role responsibility elements based on task objectives, task inputs, task outputs, and pre- and post-task constraints, generate responsibility vectors, and construct a verifiable responsibility graph; Based on the responsibility graph, the task entry parameters, task exit parameters, quality limit parameters and traceability parameters are compiled to generate an executable contract, and the fingerprint generated by the executable contract is bound to the corresponding responsibility vector. Based on contract binding, real-time consistency verification data is collected, and verification data packets are injected at the moment of role switching to verify whether the constraints of the currently executable contract are met. If not, the responsibility graph is traced back and correction suggestions are generated. Based on the proposed corrections, bidirectional semantic alignment is performed on the handover documents, task parameter sets, and task runtime environment status. The consistency verification data is integrated with the verification results of the executable contract to generate a handover consistency proof. Under the constraint of handover consistency proof, a task responsibility graph perturbation model is constructed to simulate personnel replacement events, task priority change events, and external role intervention events. Based on the simulation results, the task execution path is rearranged to identify potential risks of broken responsibility chains. Based on the simulation results, a handover shadow path parallel to the main task flow is established, and counterfactual trajectory verification is performed. If the trajectory deviation exceeds the preset threshold, the system switches to the optimal alternative contract path and injects micro-delay anchors to complete the closed-loop repair of the responsibility chain.

[0007] Preferably, the steps for constructing the responsibility graph are as follows: Obtain the structural description information of the task to be assigned, and extract the task objective, task input fields, task output fields, task pre-constraints, and task post-constraints; Based on the task structure description information, identify the responsibility elements of the participating roles and construct a responsibility vector that includes role identifier, triggering premise, output fields, task target subset and output docking role; The responsibility vectors are organized into nodes in a graph structure. A responsibility chain topology is constructed through directed edges between nodes, forming a responsibility graph with associated field mappings, execution order, and behavioral constraints. The responsibility graph is subjected to integrity verification, loop closure detection, and path summary generation to obtain a graph structure hash identifier containing node sequence, field sequence, and execution order, which serves as the structural basis before task execution.

[0008] Preferably, the steps for generating an executable contract and binding it to the corresponding responsibility vector are as follows: Extract the parameters of each responsibility vector from the responsibility graph that match the role's task execution, including task entry parameters, task exit parameters, quality limit parameters, and traceability parameters, to form a complete set of execution fields; Based on the set of execution fields, semantic classification and syntax verification are performed, and the data is structured and compiled into an executable contract document that includes input conditions, execution requirements, delivery standards, verification mechanisms and traceability paths; A digital fingerprint is generated for the executable contract document, and the fingerprint value, generation time point and constraint content summary are embedded into the corresponding responsibility vector to establish a two-way binding relationship between the contract fingerprint and the responsibility vector. The responsibility vectors that have been bound to the contract fingerprints are remapped into the responsibility graph, and the fingerprint verification process is configured in the execution path to achieve dynamic verification of contract validity and behavioral consistency.

[0009] Preferably, the steps for collecting real-time consistency verification data and generating correction suggestions based on contract binding are as follows: Based on the responsibility vector structure of the contract-bound responsibility graph, task execution data before role switching is collected, contract entry fields are extracted to construct an input data structure table and generate real-time data snapshots. A complete verification data packet is injected at the moment of role switching, and the field constraints in the executable contract are compared item by item to generate a field-level consistency verification report; If the verification report contains a default field, the responsibility graph backtracking mechanism is triggered, and a set of repair suggestions is generated by combining the default field path, which includes responsibility vector number, field correction instruction, path adjustment suggestion and role replacement suggestion; The repair suggestions are mapped into the current task flow, the responsibility graph path structure is reconstructed, the contract fields are updated and fingerprints are regenerated, ensuring that the responsibility chain achieves closed-loop repair and execution continuity assurance in dynamic abnormal scenarios.

[0010] Preferably, the path adjustment suggestions included in the repair suggestion set are limited to removing the existing connections between responsibility vectors and rebuilding new connections that satisfy the constraints, and the updated responsibility graph must be re-executed after the path adjustment is completed. Figure 1 Consistency verification is performed to ensure that adjustments do not introduce new risks of chain breakage.

[0011] Preferably, the steps for generating a handover consistency certificate are as follows: Based on the revised recommendations, extract responsibility vector pairs involving role handover, load the handover documents and task parameter sets, perform field-level semantic alignment, and mark semantically consistent and semantically conflicting fields; For semantically conflicting fields, the system verifies the data by combining it with the task runtime environment status data, determines whether the generation process of the field value is consistent with the current task chain, and generates a field verification report. By integrating the semantic alignment results, status verification results, and contract verification results, a handover consistency certificate document is generated, which includes role information, field comparison details, status verification conclusions, and contract consistency scores.

[0012] Preferably, the steps for identifying potential risks of a broken chain of responsibility include: Extract the responsibility vector number that has been confirmed to have been handed over from the handover consistency certificate, and construct a snapshot of the responsibility graph status of the current task; Based on the snapshot of the graph status, three types of disturbance scenarios are constructed: personnel replacement scenario, task priority change scenario, and external role intervention scenario, and responsibility graph disturbance instances are generated. Path rearrangement is performed based on each instance of responsibility graph perturbation, adjusting the start and end positions of the affected responsibility segments and constructing a new responsibility flow sequence; The input and output fields, role capabilities, and contractual relationships of the rearranged path are compared node by node to identify the risk points of chain breakage such as field mismatch, capability insufficiency, and handover failure. Generate a stability assessment report for the task disturbance scenario, which includes the disturbed responsibility vector, the old and new path structures, the cause of the chain break, recovery suggestions, and stability scores.

[0013] Preferably, the steps to complete the closed-loop repair of the chain of responsibility are as follows: Based on the perturbation calculation results, candidate paths with high structural overlap are extracted, and shadow handover paths parallel to the main task path are constructed and attached to the responsibility graph. During the execution of the main task, the behavior trajectory of the responsible node is collected, and the field structure, time consistency and contract status are compared with the predefined behavior pattern in the shadow path to generate trajectory offset data and monitor the offset trend. When the trajectory offset value exceeds the threshold, the shadow path with the best structural integrity, contract coverage capability and cost prediction is selected to replace the main path, and field migration, role switching and execution status reconnection operations are performed. Micro-delay anchor points are set before and after the path switching point. The scheduling window is fine-tuned through time gaps and a responsibility chain reconnection adjustment instruction is generated to complete the closed-loop repair of the responsibility chain and update the responsibility graph structure status.

[0014] The technical effects and advantages provided by the present invention in the above technical solution are as follows: This invention effectively constructs a task execution chain with a verifiable responsibility structure, enabling closed-loop control over the responsibility boundaries, contract fulfillment, semantic consistency, and temporal continuity during the cross-role task breakdown and handover process in complex, variable, and dynamically reconfigurable work environments. This method not only achieves structural visualization and logical verification of the role behavior chain through responsibility graph modeling but also introduces an executable contract fingerprint binding mechanism to ensure traceable and verifiable contractual basis for task execution. Furthermore, through real-time consistency verification and counterfactual shadow path verification, it dynamically identifies potential responsibility chain break risks and proactively intervenes to repair them. For the first time, it achieves an integrated control mechanism of "continuity detection—break prediction—replacement execution—anchor point repair" for the responsibility chain in a multi-role task scheduling scenario. This solution significantly improves the stability of task scheduling, the reliability of the execution process, and the rapid self-healing capability of abnormal situations, fundamentally overcoming the technical deficiencies of existing technologies that lack continuity verification and chain break identification methods for task responsibility transfer. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0016] Figure 1 This is a flowchart of the task assignment method for a multi-role employment model according to the present invention. Detailed Implementation

[0017] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0018] This invention provides, for example Figure 1 The task assignment method shown for a multi-role employment model includes the following steps: Establish a responsibility chain topology, extract cross-role responsibility elements based on task objectives, task inputs, task outputs, and pre- and post-task constraints, generate responsibility vectors, and construct a verifiable responsibility graph; To achieve structural visibility, logical verification, and dynamic traceability of the responsibility chain in multi-role collaborative tasks, a complete and verifiable responsibility chain topology needs to be established before task execution, clearly defining the task objectives, inputs and outputs, constraints, and the responsibility transfer relationships between roles. The specific implementation process includes the following steps: The process involves acquiring the structural description information of tasks to be assigned, extracting task objectives, input fields, output fields, pre-constraints, and post-constraints item by item. Task objectives are semantically parsed and categorized, transforming natural language descriptions into structured tags. For example, "Complete machine tool accuracy verification in the workshop" is parsed as "Equipment-type task - Verification type - Accuracy target 0.01 mm". Task input fields must be clearly defined, including the required operation permission level, the ability requirements of participating roles, time window limits, and resource usage status. Task output fields require pre-defined data structure standards, such as Boolean state variables, floating-point precision values, or document-type files, and it must be determined whether they constitute input conditions for downstream tasks. Pre-constraints define the state or result conditions that must be met before task execution, such as "Upstream task completed equipment preheating" or "Tool verification successful". Post-constraints clarify the stable state or scope of influence that needs to be formed after the task is completed, such as "Output device status label is available" or "Record task result file path". This structured process provides a precise semantic and data input foundation for subsequent responsibility boundary delineation, field transfer modeling, and behavioral relationship construction.

[0019] Based on a clear understanding of the task structure elements, identify the responsibilities of all participating roles in the task and construct responsibility expression units across roles, forming a set of responsibility vectors. Each responsibility vector should consist of five components: first, a unique identifier for the responsible role; second, the triggering prerequisites that the role must meet to execute the task, such as the upstream field status meeting "inspection completed"; third, the fields or document content that the role needs to output during responsibility execution, such as "equipment operating parameter record"; fourth, the task objective corresponding to the responsibility sub-behavior, such as "achieve equipment accuracy calibration"; and fifth, which subsequent role will receive the output of the responsibility behavior and in what structure the interface will be, such as "pass the output parameter form to the quality inspection role". In actual construction, it is necessary to establish field types, structural hierarchies, unit standards, and legal value ranges for the input and output fields of each responsibility vector. For example, if role A is responsible for equipment configuration and the output field is "configuration completed = TRUE", then role B must be able to accept a Boolean type structure when receiving it, and the response logic must identify the TRUE value as a task initiation signal. This step ensures that cross-role responsibility elements are not only semantically related, but also verifiable in terms of field structure and execution behavior.

[0020] All responsibility vector structures are organized in a graph structure to construct a complete responsibility chain topology and generate a responsibility graph. Each responsibility vector corresponds to a structural node in the graph. This node contains role information, input conditions, output fields, and target correspondences. Nodes are connected by directed edges to form a transmission link for responsibility behaviors in the task. These edges not only express the sequential relationship of "responsibility A is passed to responsibility B," but also clarify the field mapping table, triggering order, and verifiable constraints. For example, the field "Field X = Parameter Group Y" output by node N1 will be passed to the input field "Field Z" of node N2 through directed edge E1. This edge must contain a field transformation relationship: "Field X → Field Z," with the unit changing from "milliamperes" to "amperes," and the structure deconstructed from an array form into single-valued fields. Each path in the responsibility graph must undergo structural consistency verification, temporal sequence verification, and semantic relationship verification to ensure the integrity, operability, and logical coherence of the path. Simultaneously, the graph structure must retain the source information, version status, and field update records of each node to support subsequent structural calls during contract generation, responsibility verification, and execution verification processes.

[0021] The completed responsibility graph undergoes integrity verification, closed-loop structure detection, and stability solidification. Integrity verification checks for disconnected nodes, dead ends where fields cannot be passed on, or missing role responsibilities. Closed-loop structure detection confirms that each responsibility path forms a closed behavioral loop from initial input to final output, and checks for broken field transmission or idle responsibilities. Stability solidification generates a structural summary value for each path, including node sequence, field type sequence, role execution order, and field interrelationships, and generates a graph structure hash identifier from the summary value. This identifier is used for rapid matching, version control, and execution constraint binding in subsequent processes. The final responsibility graph will serve as one of the core input structures for the task scheduling engine, providing a complete structural foundation for subsequent executable contract compilation, handover consistency verification, task path simulation, and chain break repair.

[0022] Based on the responsibility graph, the task entry parameters, task exit parameters, quality limit parameters and traceability parameters are compiled to generate an executable contract, and the fingerprint generated by the executable contract is bound to the corresponding responsibility vector. To achieve verifiable responsibility and strong constraint control over role behavior during task execution, the execution elements of each node in the graph need to be transformed into structured, traceable, and verifiable execution contracts, and the contract fingerprints need to be bound to the corresponding responsibility vectors. Specifically, this includes the following steps: Based on the constructed responsibility graph structure, extract the set of parameters directly related to the task execution of the role from each responsibility vector node. These parameters mainly include four parts: task entry parameters, task exit parameters, quality limit parameters, and traceability parameters. The extraction process of task entry parameters includes identifying the original input data fields on which the task depends, such as: the path of the intermediate data file generated by the previous role, the structure definition of the data, the data version number, the resource acquisition method, the task start conditions, the environment variable values, the start and end times of the operation window, and necessary verification identifiers; task output parameters include the list of data objects to be produced after execution, such as the format definition of the output result, the storage path, the target receiving object, the data encryption status, the task end timestamp, the execution status code, and the identifier that triggers downstream tasks; quality constraint parameters include the agreed-upon indicator constraints during task execution, such as the temperature fluctuation range, voltage stability value, error tolerance range, calibration status confirmation flag, key detection points in the execution process, and their pass / fail standard values; the extraction of traceability parameters focuses on the data used for subsequent responsibility tracking, including the role identification code, task instruction number, the set of timestamps for the execution process, the responsibility vector number, the input and output data signature values, the task link ID, the coordinate number of the location where the role's behavior was executed, and the execution device identification code. These fields are precisely extracted by parsing the handover content and constraints of the role participation edges in the responsibility graph, ensuring that each parameter is measurable, structurally clear, and verifiable, providing complete data support for subsequent contract generation.

[0023] After the parameter set is extracted, it needs to be structured and compiled into a task contract with execution constraints. This process first semantically categorizes the extracted parameter fields into five main categories: input conditions, execution requirements, delivery criteria, verification mechanisms, and traceability paths, with specific field instances corresponding to each category. For example, in the input conditions category, the "resource file path" field and the "environment variable name" field form a data availability verification sub-segment; in the delivery criteria category, the "output data structure number," "storage directory integrity verification value," and "target receiving role number" are combined into a delivery matching rule sub-segment. Subsequently, a unified field semantic encoding format is used for each category of fields, such as using "RDATA_IN_PATH" to represent the input path, "QCHECK_RANGE_MAX" to represent the quality upper limit, and "ROUTE_CHAIN_ID" to represent the task responsibility chain number. These fields are then embedded into the corresponding entries in the contract template. The contract template consists of several executable clauses, each expressing the triggering conditions and execution consequences using an "if...then..." structure. For example: "If the input parameter RDATA_IN_PATH fails the integrity verification, the activation state of the responsibility vector corresponding to that role will be terminated and error code Q_ERR_003 will be recorded." After the contract structure is generated, all field values ​​and logical statements are subjected to syntax validation and logical consistency checks to ensure that there are no redundant fields, ambiguous expressions, or logical conflicts. The final contract document is a structured, logically closed, semantically unique, and field-complete execution contract document, capable of directly participating in task scheduling process control.

[0024] To ensure the uniqueness and tamper-proof nature of contract documents, a digital fingerprint is generated for each contract document, and this fingerprint value is written into the corresponding responsibility vector structure to achieve a two-way binding between responsibility and contract. The digital fingerprint is generated using a standard encrypted digest mechanism. All fields in the contract (including field names, field values, logical expressions, timestamps, execution constraint numbers, etc.) are structurally concatenated to form a unique data string. This data string is then digested to obtain a 128-bit irreversible unique identifier value as the contract's fingerprint. Subsequently, three fields are added to the responsibility vector structure: a bound contract fingerprint field, a contract generation time field, and a contract content digest field, recording the contract's digest value, generation time, and a summary description of the constraint content, respectively. This binding operation ensures a one-to-one correspondence between the role's behavioral constraints in the responsibility vector and the contract content, making them indivisible and verifiable. At this point, the responsibility vector not only carries the role's task information but also has binding behavioral boundaries and verification benchmarks, enabling the fingerprint information to be used for consistency checks during subsequent role activation, behavior switching, and handover confirmation processes.

[0025] After contract generation and fingerprint binding are completed, the bound responsibility vectors are remapped into the original responsibility graph, and a contract verification process is established in the execution path. Before each responsibility vector is activated, this process calls the fingerprint verification mechanism to read the contract fingerprint value recorded in the responsibility vector. Simultaneously, a real-time summary is generated for the current parameter environment, and the fingerprint is compared. If the comparison matches, and the contract generation time field does not exceed the time limit constraint, the role identity has not been revoked, and the task status meets the start conditions, then the responsibility vector is allowed to enter the execution state. Otherwise, the responsibility vector is marked as an abnormal state, the abnormality type is recorded, and the responsibility graph backtracking mechanism is triggered. Through this process, a strongly constrained pre-execution verification mechanism is established during task execution, significantly enhancing the contract rigidity guarantee capability of the task responsibility chain and preventing execution errors or responsibility breaks caused by contract failure or contract separation from the responsibility vector.

[0026] Based on contract binding, real-time consistency verification data is collected, and verification data packets are injected at the moment of role switching to verify whether the constraints of the currently executable contract are met. If not, the responsibility graph is traced back and correction suggestions are generated. To ensure the continuity of the multi-role task responsibility chain and the effective execution of contractual constraints during role switching, it is necessary to collect real-time consistent data on the task execution environment based on the responsibility vector binding contract. A verification process should be triggered at the moment of role switching to promptly identify unmet contractual conditions and pinpoint the breakpoint in the responsibility chain, thereby generating accurate remediation suggestions. Specifically, this includes the following steps: Based on the responsibility vector structure of the bound contracts, the responsibility vector number of the upcoming role switch is identified, and the connection edge between the previous and next responsibility vectors corresponding to that number is obtained. This connection edge records the role handover relationship, the switching timing requirements, the type of event triggered by the handover, and the handover direction. After obtaining this edge, the entry conditions in the contract bound to the next responsibility vector are parsed, and the environmental parameter fields that need to be satisfied are extracted to form the expected input data structure table. This structure table includes field identifiers, data type definitions, allowed value ranges, source responsibility numbers, expected delivery timestamps, task identifiers, and field hash verification values. According to the fields listed in the structure table, the actual data existing in the current task execution environment is collected in real time to form a data collection snapshot, recording the current value of each field, the value generation time, the generating responsibility party identifier, the data storage location identifier, and the data integrity label. Through this collection process, it is ensured that the data source used in subsequent contract verification operations is traceable, verifiable, and highly time-sensitive, preventing the risk of verification judgments based on expired or erroneous data.

[0027] Upon detecting a change in role status from "Execution Terminated" to "Pending Handover," a data verification process is triggered via precise control signals, injecting a complete verification data packet in a structured manner. This data packet is packaged item by item according to the field definitions in the preceding snapshot, and its structure includes field name, collected value, standard value comparison result, constraint satisfaction flag, value generation time, and the field number and responsibility vector number corresponding to the current contract. The injection method involves directly embedding the data packet into the role switching scheduling process through a synchronous pipeline, ensuring that it is injected and executed before the scheduling control flow executes its judgment logic. During execution, the contract terms bound to the current responsibility vector are called item by item, and their entry conditions and logical judgments are read. Taking the field "Input Data Integrity Label" as an example, if the contract terms require the field value to be "OK" and generated within 5 minutes, the system will read the corresponding field value in the data packet and perform a consistency comparison operation. If the field value is "INVALID" or the timestamp exceeds the allowed window, the contract terms are deemed unsatisfactory, and a field breach identifier is generated. Field-level breach information includes the breaching field number, breach type (value mismatch, time mismatch, source error), field generation location, and the length of the affected responsibility path. After integrating the default results of all validation fields, a complete contract consistency validation result report is generated.

[0028] If any clause in the contract consistency verification report is not met, the responsibility graph backtracking mechanism is immediately triggered to identify the upstream responsibility break path that caused the current contract non-compliance. The backtracking mechanism starts from the current responsibility vector and sequentially searches for all predecessor responsibility vectors along the connecting edges in the graph, prioritizing the responsibility outputs related to the default fields. Taking the field "data file path" as an example, if a path is determined to be missing, the backtracking path will first search for the predecessor responsibility vector that produced the data for that path, verifying whether its output parameters contain the path definition and determining whether its execution status is "successful." If the path has indeed not been created, it is determined that the responsibility vector has an execution omission. If the path exists but the data format is incorrect, it is further checked whether the output format definition of the responsibility vector is consistent with the output behavior execution content. Each level of backtracking includes a path number, related field identifiers, responsibility number, and execution status record, forming a backtracking trajectory table. Combining the data in the trajectory table, remediation suggestions are generated through behavioral path causal chain analysis. The remediation recommendations include: responsibility vector numbers for which delivery fields need to be supplemented, responsibility vector numbers for which execution is recommended to be reactivated, field names for adjusting input parameter structures, recommended handover timing with a delayed time window, recommended standard values ​​for validation formats, recommended responsibility edge redirection path numbers, and a list of non-essential responsibility vector numbers for which termination is recommended, along with a list of recommended replacement role numbers. All recommendations are expressed as a data structure sequence to ensure they can be directly invoked and participate in subsequent responsibility chain adjustment execution flows.

[0029] The generated repair suggestions are delivered to the current task execution flow control, dynamically adjusting and correcting the responsibility graph at the flow level. First, based on the "responsibility vector number needs to be reactivated" instruction in the suggestion, a retry task execution instruction is inserted into the role scheduling time window corresponding to that number and marked as "backtracking triggered type." Second, for fields in the suggestion that "input fields need correction," the data source collection mechanism is triggered and validation logic is added to ensure they meet contract requirements in the new window. Third, for structures containing "edge path redirection" content in the suggestion, graph path editing operations are performed, removing the original connecting edges between responsibility vectors and creating new connecting edges that conform to the suggested path, ensuring that the responsibility flow continues to be transmitted from the recommended path direction. Fourth, the time window parameters, quality threshold fields, and receiving role identity fields in the contracts bound to the responsibility vectors are reset, and new fingerprints are generated after rebinding the contracts. Fingerprint comparison ensures that the contract status is updated and the content is consistent. Finally, the current responsibility graph is fully... Figure 1 Consistency verification checks whether the new path introduces additional risks of chain breakage. If the verification passes, the process continues with the adjusted path. This complete closed-loop mechanism not only enables real-time detection and repair of task responsibility breaks, but also links the task responsibility chain with the dynamic anomaly in real time, greatly enhancing its fault tolerance and adaptive control capabilities.

[0030] Based on the proposed corrections, bidirectional semantic alignment is performed on the handover documents, task parameter sets, and task runtime environment status. The consistency verification data is integrated with the verification results of the executable contract to generate a handover consistency proof. To ensure semantic consistency and clear responsibility boundaries in information transmission during multi-role task handover, after completing contract verification and responsibility backtracking, it is necessary to perform bidirectional semantic alignment of handover documents, parameter sets, and operational status based on the proposed corrections, and integrate the verification data with the contract comparison results into a handover consistency certificate. This process includes the following operations: Based on the generated set of correction suggestions, responsibility vector pairs involving role handover are extracted. The document content generated by the source role at the end of its task execution phase and the parameter set pre-configured by the target receiving role at the beginning of the task are loaded respectively. A one-to-one mapping relationship is established based on field-level semantic parsing rules to align the document and parameter content. The handover documents include a task output confirmation list, a deliverable structure definition table, a handover behavior description record, a responsibility transfer statement, and a signature verification page. The task parameter set includes a receiving task entry list, preset input field configurations, an execution control parameter table, a semantic annotation set, and a field structure definition table. Through field attribute comparison and structure definition parsing, the field names, data structures, value ranges, business semantic descriptions, and operational contexts in both types of documents are parsed item by item, and alignment matching operations are performed. Taking the "Quality Inspection Conclusion Report Number" field in the handover document as an example, it is compared with the "Quality Inspection File Code" field in the task parameter set to determine whether they are consistent in semantic interpretation, field value format, data content generation time, and acceptable range. Fields that match perfectly are marked as "semantic alignment confirmed fields"; fields with semantic discrepancies, structural conflicts, or inconsistent use cases are marked as "semantic alignment failed fields," and the field number, field source, expected field semantics, current field semantics, and conflict type label are output. Through the above field comparison process, a preliminary handover semantic mapping list is generated, providing structural support for subsequent data consistency verification.

[0031] For fields marked as pending verification or aligned failure in the semantic mapping list, semantic verification is performed in conjunction with the current task runtime environment status data. Runtime status data sources include, but are not limited to, task runtime time-series information, snapshots of execution equipment parameters, tool usage records, personnel on-duty behavior trajectories, data generation source paths, runtime environment stability logs, and on-site task physical status perception data. Taking the "Tool Calibration Confirmation Status" field as an example, if the handover document marks it as "calibrated," but the runtime status data shows that the tool was not called or generated a calibration timestamp during the task execution cycle, then the semantics of this field are determined to be "inconsistent between the handover document and the runtime status"; otherwise, it is confirmed as a "successfully semantically verified handover status field." This comparison not only verifies the consistency of the current field value but also needs to comprehensively determine whether it truly originates from the current handover task chain by combining the generation time, data acquisition path, responsible role number, and task segment number. All fields involved in the verification process are ultimately categorized as either "fields successfully confirmed" or "fields failing to confirm," and a field verification report is generated, listing the field's unique ID, the target field ID, the verification data source, the verification result, the verification timestamp, and the verification reliability score. This approach differs from existing solutions that only compare data values; for the first time, it uses process data as the pragmatic verification basis for semantic alignment, ensuring that each field has a genuine source, a reasonable context, and execution meaning, greatly improving the completeness and credibility of the information handover alignment.

[0032] After completing semantic mapping and state verification, the final consistency proof generation stage begins, constructing a structured handover consistency proof document. This proof document contains five parts: the first part is the handover role information area, recording the responsibility vector number, role number, role type description, duty description, and handover timestamp of both parties; the second part is the semantic alignment report area, listing all alignment fields, including the original field number, field source document, corresponding receiving field number, alignment type, semantic interpretation comparison result, and alignment status; the third part is the runtime status verification area, listing all fields involved in the verification, including the state source number, field execution interval, data generation path, field verification conclusion, and credibility score; the fourth part is Contract One. The consistency integration area summarizes the comparison results of all clauses in the previous stage contract verification report, links each field with its corresponding contract clause number, and displays the current status and constraint satisfaction of the field. The fifth part is the final judgment conclusion area, which outputs a comprehensive handover consistency score based on semantic alignment success rate, status verification success rate, and contract clause satisfaction, generates a final conclusion flag, and indicates whether the current handover meets the execution conditions, whether it is recommended to continue the task flow, and whether an additional review process needs to be triggered. It also includes the electronic signature digest of the current proof document, the generated timestamp, the data source list, and the responsibility confirmation chain. Through this structured proof, the current handover behavior has complete responsibility support and data verification chain, and can serve as authoritative evidence for subsequent task execution, responsibility determination, or anomaly handling.

[0033] Under the constraint of handover consistency proof, a task responsibility graph perturbation model is constructed to simulate personnel replacement events, task priority change events, and external role intervention events. Based on the simulation results, the task execution path is rearranged to identify potential risks of broken responsibility chains. To ensure the stability and continuity of the multi-role task responsibility chain in the face of unforeseen events, after generating the handover consistency proof, a responsibility graph perturbation model needs to be constructed based on its constraints. Scenario calculations are then used to predict the risk of responsibility chain breakage, and path rearrangement and stability assessment are completed. Specifically, this includes the following steps: The system reads the structured data from the handover consistency proof, extracts the responsibility vector numbers of all confirmed completed handovers, and synchronously loads the graph edge connection information between these responsibility vectors to form a set of known responsibility paths for the current task. This path set includes the connection order between responsibility vectors, responsibility transfer triggering conditions, the identity identifiers of each node's role, job descriptions, contract constraint field numbers, handover field confirmation status, task entry timestamps, and output result structure descriptions. During path construction, the input and output field structures of each responsibility node are bidirectionally labeled with the node's contract clause number, and the corresponding field positions of the handover fields in the preceding and following roles are also marked. Status annotation is performed on each responsibility vector, and its delivery behavior is recorded as having passed the consistency proof verification. Finally, a complete graph state snapshot is formed. This snapshot not only records the structural path relationships but also includes executable behavior information, field flow status, and semantic links of handover edges, providing a structured input foundation for subsequent perturbation construction.

[0034] Based on the snapshot of the task responsibility graph status, three high-risk disturbance scenarios are constructed: personnel replacement scenario, task priority change scenario, and external role intervention scenario. The personnel replacement scenario refers to replacing a confirmed responsible role with another candidate role with similar responsibility labels. The replacement process includes changing the role number, loading the role's historical responsibility records, assessing contract performance capabilities, and reconstructing field capability mappings. The task priority change scenario involves inserting a set of higher-priority task responsibility vector nodes into the original execution path. This change causes time resource conflicts, node delays, or overlapping execution windows in the original path. The external role intervention scenario involves inserting a role not registered in the initial task plan into the graph, making it assume some of the execution behaviors corresponding to the responsibility vector nodes in the original task. The process includes role identity generation, responsibility attribution registration, field data channel allocation, and dynamic generation of the new contract structure. All three disturbance scenarios are injected into the original graph in a structured manner, generating a set of responsibility graph disturbance instances for each, and recording the role changes, field access adjustments, and connection relationship changes for each instance.

[0035] Based on each perturbation graph instance, a path rearrangement operation is performed, reconstructing the original task path into a new responsibility flow sequence according to the perturbation state. Path rearrangement is based on node executability, determining whether the perturbation-required responsibility vectors meet the integrity requirements of task input fields, the handover matching degree of output fields, the adaptability of roles and contracts, and the resource availability of the execution time window. During the rearrangement process, unaffected responsibility segments in the original path are retained, the start and end positions of affected segments are adjusted, and alternative node chains are sought to supplement broken paths. For example, if the original role of a responsibility node is replaced, its output fields no longer meet the type requirements of subsequent node input fields, then other alternative responsibility vectors need to be found in the graph to connect the paths, or bridging nodes need to be added to complete the field reconstruction operation. Each path rearrangement generates a new path structure, indicating the path start point, end point, rearrangement reason, adjusted node number, adjusted field number, and a comparison table of responsibility chain numbers before and after adjustment. Through path rearrangement, not only are new task execution paths under the influence of perturbation constructed, but also an execution foundation is established for the next step of chain break risk identification.

[0036] For each new path after the disturbance, a responsibility chain integrity analysis is performed to identify all potential responsibility break risk points. The criteria for judging responsibility break risk include, but are not limited to: field missing risk, field semantic mismatch risk, execution capability insufficiency risk, responsibility overlap risk due to time conflicts, and handover edge connection failure risk. The specific analysis method involves traversing each responsibility vector node on each path, comparing its output fields with the input fields of subsequent nodes to ensure consistency in field structure, field type, value range restrictions, time requirements, and semantic interpretation; comparing its execution constraints to match the current role's capabilities, scheduling window, and authorized scope; and verifying that each handover edge connection satisfies handover field consistency, contract acceptance validity, and path triggering condition continuity. If any indicator is not met, it is marked as a "chain break risk point," and the break type, break field number, upstream and downstream node numbers of the break field in the graph, role identity number, contract clause number, and scheduling time of the break occurrence are recorded. All chain break risk points are marked in the graph, and a chain break risk heatmap is generated to quantitatively assess the overall stability of the graph.

[0037] Based on the heatmap of chain break risks and path rearrangement analysis results, a stability assessment report for task disturbance scenarios is generated. The report includes five parts: Part 1 lists all disturbed responsibility vector numbers and their original and new states; Part 2 shows the rearranged execution path chains and corresponding adjustment instructions; Part 3 details all identified responsibility chain breaks and their cause classifications; Part 4 outputs chain break recovery suggestions, including recommendations to replace role numbers, add fields to bridge responsibility segment numbers, reset field input / output formats, and adjust execution window times; Part 5 outputs the overall stability score and responsibility chain robustness index. The overall stability score is derived by calculating the density of chain break points, path recovery costs, and the distribution ratio of chain break points in key task execution segments, and outputs control flags indicating whether task execution can continue, whether a pause adjustment is needed, and whether task plan regeneration should be triggered. This report serves as a risk prediction tool during the task evolution phase, providing decision-makers with quantitative basis for task scheduling, role allocation, and path planning, effectively avoiding task failures caused by implicit responsibility chain breaks due to sudden disturbances.

[0038] Based on the simulation results, a handover shadow path parallel to the main task flow is established, and counterfactual trajectory verification is performed. If the trajectory deviation exceeds the preset threshold, the system switches to the optimal alternative contract path and injects micro-delay anchors to complete the closed-loop repair of the responsibility chain. To ensure timely identification and adaptive repair of responsibility chain anomalies during mission execution in the event of trajectory deviation, a shadow handover path for the main mission flow needs to be established based on simulation. This is achieved through parallel trajectory monitoring and counterfactual verification to ensure closed-loop stability of the mission responsibility chain. This process includes the following steps: Based on the rearranged path set generated by perturbation calculation, candidate paths with high structural overlap with the current main task path are extracted to establish shadow handover paths that run in parallel with the main path. The construction of shadow paths is not a simple replication of the main path structure, but rather a full field mapping based on the input fields, output fields, execution order, role capability level, contract matching degree, and field semantic interpretation of each responsibility vector in the main path. During the construction process, a role substitute needs to be re-matched for each responsibility node in the shadow path to determine whether it has equivalent field processing capabilities, task scheduling window, and contract fulfillment qualifications. For example, if the responsibility vectors in the main path... Executed by role A, the same structure vector in the shadow path This task should be undertaken by role B, and it must be verified whether role B possesses the necessary qualifications. The system must be able to parse the input and output fields required by the contract terms. Each shadow path must have an independent contract binding identifier, field structure encoding, and execution condition triggering rules. After construction, the main task path and shadow paths are synchronously attached to the task responsibility graph, forming a comparable and switchable parallel trajectory execution environment.

[0039] After the main task flow enters the actual execution phase, its behavioral trajectory is continuously recorded at the responsibility vector level, including but not limited to task trigger timestamps, actual values ​​of input fields, field arrival time differences, output field structures, role execution confirmation signatures, quality threshold judgment results, and the downward transmission status of handover fields. This trajectory data is compared in real-time with predefined behavioral patterns of the same nodes in the shadow path, forming a counterfactual trajectory verification mechanism. This mechanism identifies the degree of behavioral deviation between each node in the main path and its shadow node through field structure comparison, time consistency judgment, and contract status synchronization analysis. For example, when the nesting depth of an output field of a responsibility node in the main path does not match the expected depth of that field in the shadow path, the system determines it as a field structure deviation; when a role switching delay exceeds a preset millisecond threshold, it is recorded as a handover timing deviation. The trajectory deviation data generated by each comparison is structured and summarized according to field number, node number, deviation value, deviation type, and responsibility vector index, and a trajectory deviation trend chart is constructed. When the trend chart shows that the cumulative deviation value exceeds the predefined threshold curve, it is automatically determined that the current main path is no longer stable, triggering the path replacement preparation process.

[0040] When a significant deviation from the main path is detected, or execution is interrupted at a node due to field mismatch, invalid contract constraints, or role unavailability, the optimal alternative path for the current stage is immediately selected from the shadow path set. The selection logic comprehensively considers four indicators: first, the structural integrity of the responsibility vector in the path, i.e., whether field transmission is coherent and whether role connections have a behavioral loop; second, the predicted execution cost in the path, including time consumption assessment, role idle window calculation, and resource utilization; third, the coverage capability of contract constraints, determining whether the alternative path contains all the behavioral clauses that should be fulfilled in the main path; and fourth, the historical simulation evaluation score, i.e., the path's breakage probability, reconstruction cost, and semantic consistency score during the initial perturbation calculation phase. After the path is determined, the system disconnects the current task from the main path breakage node, connects it to the corresponding responsibility node in the shadow path, and performs field data migration. During the migration, all incomplete fields in the main path are imported into the field receiving buffer of the shadow path node through structural mapping relationships. Simultaneously, role behavior switching, contract fingerprint rewriting, execution timeline correction, and task control parameter resetting are completed to ensure continuous behavioral logic, consistent data structure, and complete execution status during the switching process.

[0041] To ensure that path replacement does not disrupt the closed-loop nature of the task responsibility chain on the timeline, micro-delay anchor points need to be set on both sides of the path switching point to achieve precise alignment between the responsibility chain structure hierarchy and the time sequence. The forward anchor point is set at the tail of the upstream node where the trajectory offset occurs, used to record the last field output time, field structure snapshot, and responsibility transfer status when the main path actually terminates. The backward anchor point is set before the shadow path entry node, used to set the field input buffer time, role activation waiting window, and contract initialization time threshold. The time difference between the two anchor points is the "logical time gap." The system uses this value to generate a "responsibility chain reconnection adjustment instruction," fine-tuning the scheduling windows of upstream and downstream nodes and introducing synchronization control signals to maintain consistent execution chain progress. Finally, this anchoring behavior and the complete migration path are written together into the task execution archive document, marking the current process as "closed-loop repair successful," and updating the structural status in the responsibility graph as "fractured self-healing path."

[0042] The task assignment method described above, designed for multi-role employment models, effectively constructs a task execution chain with a verifiable responsibility structure. This enables closed-loop control over the responsibility boundaries, contract fulfillment, semantic consistency, and temporal continuity during the cross-role task breakdown and handover process in complex, dynamic, and reconfigurable employment environments. This method not only achieves structural visualization and logical verification of the role behavior chain through responsibility graph modeling but also introduces an executable contract fingerprint binding mechanism to ensure traceable and verifiable contractual basis for task execution. Furthermore, through real-time consistency verification and counterfactual shadow path verification, it dynamically identifies potential responsibility chain break risks and proactively intervenes to repair them. For the first time, it achieves an integrated control mechanism of "continuity detection—break prediction—replacement execution—anchor point repair" for the responsibility chain in a multi-role task scheduling scenario. This solution significantly improves the stability of task scheduling, the reliability of the execution process, and the rapid self-healing capability of abnormal situations, fundamentally overcoming the technical deficiencies of existing technologies that lack continuity verification and chain break identification methods for task responsibility transfer.

[0043] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A task assignment method for multi-role employment models, characterized in that, Includes the following steps: Establish a responsibility chain topology, extract cross-role responsibility elements based on task objectives, task inputs, task outputs, and pre- and post-task constraints, generate responsibility vectors, and construct a verifiable responsibility graph; Based on the responsibility graph, the task entry parameters, task exit parameters, quality limit parameters and traceability parameters are compiled to generate an executable contract, and the fingerprint generated by the executable contract is bound to the corresponding responsibility vector. Based on contract binding, real-time consistency verification data is collected, and verification data packets are injected at the moment of role switching to verify whether the constraints of the currently executable contract are met. If not, the responsibility graph is traced back and correction suggestions are generated. Based on the proposed corrections, bidirectional semantic alignment is performed on the handover documents, task parameter sets, and task runtime environment status. The consistency verification data is integrated with the verification results of the executable contract to generate a handover consistency proof. Under the constraint of handover consistency proof, a task responsibility graph perturbation model is constructed to simulate personnel replacement events, task priority change events, and external role intervention events. Based on the simulation results, the task execution path is rearranged to identify potential risks of broken responsibility chains. Based on the simulation results, a handover shadow path parallel to the main task flow is established, and counterfactual trajectory verification is performed. If the trajectory deviation exceeds the preset threshold, the system switches to the optimal alternative contract path and injects micro-delay anchors to complete the closed-loop repair of the responsibility chain.

2. The task assignment method for multi-role employment mode according to claim 1, characterized in that, The steps for constructing a responsibility graph are as follows: Obtain the structural description information of the task to be assigned; Based on the task structure description information, identify the responsibility elements of the participating roles and construct a responsibility vector; The responsibility vectors are organized into nodes in a graph structure, and a responsibility chain topology is constructed through directed edges between nodes to form a responsibility graph. Perform integrity verification, loop closure detection, and path summary generation on the responsibility graph to obtain the graph structure hash identifier.

3. The task assignment method for multi-role employment mode according to claim 2, characterized in that, The steps to generate an executable contract and bind it to the corresponding responsibility vector are as follows: Extract parameters from each responsibility vector in the responsibility graph that match the role's task execution to form a complete set of execution fields; Based on the set of execution fields, semantic classification and syntax verification are performed, and the data is then structured and compiled into an executable contract document. A digital fingerprint is generated for the executable contract document, and the fingerprint value, generation time point and constraint content summary are embedded into the corresponding responsibility vector to establish a two-way binding relationship between the contract fingerprint and the responsibility vector. The responsibility vectors that have been bound to the contract fingerprints are remapped into the responsibility graph, and the fingerprint verification process is configured in the execution path to achieve dynamic verification of contract validity and behavioral consistency.

4. The task assignment method for multi-role employment mode according to claim 3, characterized in that, The steps for collecting real-time consistency verification data and generating correction suggestions based on contract binding are as follows: Based on the responsibility vector structure of the contract-bound responsibility graph, task execution data before role switching is collected, contract entry fields are extracted to construct an input data structure table and generate real-time data snapshots. A complete verification data packet is injected at the moment of role switching, and the field constraints in the executable contract are compared item by item to generate a field-level consistency verification report; If the verification report contains a default field, the responsibility graph backtracking mechanism is triggered, and a set of remediation suggestions is generated by combining the default field path. The repair suggestions are mapped into the current task flow, the responsibility graph path structure is reconstructed, the contract fields are updated, and the fingerprint is regenerated.

5. The task assignment method for multi-role employment mode according to claim 4, characterized in that, The path adjustment suggestions included in the repair suggestion set are limited to removing the original connection edges between responsibility vectors and rebuilding new connection edges that meet the constraints. After the updated responsibility graph is completed, the full graph consistency verification must be re-executed to ensure that the adjustment does not introduce new chain break risks.

6. The task assignment method for multi-role employment mode according to claim 4, characterized in that, The steps to generate a handover consistency proof are as follows: Based on the revised recommendations, extract responsibility vector pairs involving role handover, load the handover documents and task parameter sets, perform field-level semantic alignment, and mark semantically consistent and semantically conflicting fields; For semantically conflicting fields, the system verifies the data by combining it with the task runtime environment status data, determines whether the generation process of the field value is consistent with the current task chain, and generates a field verification report. The semantic alignment results, state verification results, and contract verification results are integrated to generate a handover consistency certificate document.

7. The task assignment method for multi-role employment mode according to claim 6, characterized in that, The steps to identify potential risks of a broken chain of responsibility include: Extract the responsibility vector number that has been confirmed to have been handed over from the handover consistency certificate, and construct a snapshot of the responsibility graph status of the current task; Based on the snapshot of the graph status, three types of disturbance scenarios are constructed: personnel replacement scenario, task priority change scenario, and external role intervention scenario, and responsibility graph disturbance instances are generated. Path rearrangement is performed based on each instance of responsibility graph perturbation, adjusting the start and end positions of the affected responsibility segments and constructing a new responsibility flow sequence; The input and output fields, role capabilities, and contractual relationships of the rearranged path are compared node by node to identify the risk points of chain breakage such as field mismatch, capability insufficiency, and handover failure. Generate a stability assessment report for the task disturbance scenario.

8. The task assignment method for multi-role employment mode according to claim 7, characterized in that, The steps to complete the closed-loop repair of the chain of responsibility are as follows: Based on the perturbation calculation results, candidate paths with high structural overlap are extracted, and shadow handover paths parallel to the main task path are constructed and attached to the responsibility graph. During the execution of the main task, the behavior trajectory of the responsible node is collected, and the field structure, time consistency and contract status are compared with the predefined behavior pattern in the shadow path to generate trajectory offset data and monitor the offset trend. When the trajectory offset value exceeds the threshold, the shadow path with the best structural integrity, contract coverage capability and cost prediction is selected to replace the main path, and field migration, role switching and execution status reconnection operations are performed. Micro-delay anchor points are set before and after the path switching point. The scheduling window is fine-tuned through time gaps and a responsibility chain reconnection adjustment instruction is generated to complete the closed-loop repair of the responsibility chain and update the responsibility graph structure status.

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