103 results about "Autonomous agent" patented technology

A symbolic neuroadaptive control system is disclosed for real-time arbitration, consent, and ethical modulation of artificial intelligence agents operating in wearable computing environments. The system integrates multimodal biometric telemetry—including high-resolution EEG signals—with a symbolic kernel that performs logic-driven arbitration over cognitive, emotional, and ethical states. Using Coq-verified invariants and zero-knowledge biometric consent tokens, the system constructs a deterministic symbolic execution graph, gating AI outputs based on internal user states such as trauma, stress, or intentionality. Unlike conventional black-box BCI models, the invention routes EEG-inferred affective-symbolic tokens through a formal ethics layer that enforces real-time interrupt control, utility bounding, and trust verification. The kernel enables AGI systems to defer or modify behavior based on user-state alignment, granting sovereign agency over all downstream actions. This neuro-symbolic architecture redefines the interface between human cognition and intelligent machines, enabling emotionally conscious, morally verifiable, and symbolically transparent AI governance in dynamic, high-stakes contexts.The present invention relates to artificial intelligence and neurotechnology, specifically to a real-time, neuro-symbolic operating system kernel that converts electroencephalography (EEG) signals into structured symbolic data for use in emotional cognition, ethical prioritization, autonomous agent dispatch, and real-time telecommunications routing. The invention bridges brain-computer interface (BCI) inputs with symbolic AI architectures to enable ethically aligned machine response during cognitively or emotionally intense events.

Systems, methods, and devices for monitoring and controlling communications between autonomous agents are disclosed. The system monitors real-time communications between autonomous agents, intercepting and recording each communication. Communications are translated to a standardized language and processed through communication protocol filters that evaluate compliance with predefined operational policies. The system parses each translated communication to identify policy violations. When violations are detected, the system modifies communications to ensure compliance with operational policies. All communications and modifications are recorded via distributed ledger technology for audit and accountability purposes. This approach enables comprehensive oversight of autonomous agent interactions while maintaining tamper-proof records of all monitoring and control activities.

A hybrid, redundant, fail-safe architecture provides a unified fail-operational framework for autonomous agents operating across physical and virtual domains. The system employs a multi-modal data source suite, an adaptive hybrid data fusion module, and an intelligent decision-making module. A novel closed-loop interaction enables a health monitoring module that detects an incipient fault in a data source by monitoring ancillary performance metrics. Upon detection, the module generates a fault signature, including a quantitative prognostic estimate of a future failure time, and transmits it to an adaptive data fusion module. The fusion module proactively reconfigures its state estimation algorithm by decreasing reliance on the degrading data source in proportion to the prognostic estimate. This preemptive compensation ensures the system maintains a high-integrity environmental model and achieves true fail-operational continuity. The architecture is applicable to numerous embodiments providing a universal solution for proactive fault management and system resilience.

The invention discloses a multi-robot cooperative measurement method and system based on crowd intelligence emergence, and aims to solve the problems of single-point fault, poor environmental adaptability and insufficient expandability in the existing centralized and pre-planned multi-robot cooperative measurement method. According to the method, a shared digital environment cooperatively and jointly maintained by all robots through decentration is constructed, a decentration task decision-making mechanism based on digital pheromones is introduced, each measurement robot is used as an autonomous agent, and the concentration of the digital pheromones dynamically determined by the quality of measurement data in the shared digital environment is sensed, so that the concentration of the digital pheromones in the shared digital environment is determined. Measurement target decisions are made independently. According to the method, a robot cluster for multi-robot cooperative measurement can spontaneously emerge a globally optimal cooperative measurement behavior without a central control node, so that the robustness, the adaptability and the expandability of a measurement system are remarkably improved, and efficient and reliable three-dimensional measurement of a large component is realized.

A computing services environment may include application servers providing computing services including access to a database system, a unified metadata framework including autonomous agent definitions referencing action definitions defining a plurality of actions capable of being performed within the computing services environment, an agent service configured to instantiate an autonomous agent instance based on an autonomous agent definition, and an orchestration layer configured to determine an orchestration plan based on novel planning text generated by a generative language model. The orchestration plan may include a subset of the plurality of actions identified in the novel planning text. The computing services environment may execute the subset of the plurality of actions within the computing services environment.

A method for risk-aware policy assessment for an autonomous vehicle can include: collecting information associated with an environment of an ego vehicle; determining a set of policy proposals; determining and assessing a set of risks encounterable (e.g., potentially encountered in the future) by the ego vehicle; selecting a policy based on the set of risks, operating the ego vehicle based on the assessed risks, and / or any other suitable elements. Additionally or alternatively, the method can include any or all of: performing a set of simulations, analyzing the simulation results, determining a set of discount profiles, discounting a set of risks, and / or any other processes. The method can be performed with a system as described below and / or any other suitable system.

A computing services environment may include application servers providing computing services including access to a database system, a unified metadata framework including autonomous agent definitions referencing action definitions defining a plurality of actions capable of being performed within the computing services environment, an agent service configured to instantiate an autonomous agent instance based on an autonomous agent definition, and an orchestration layer configured to determine an orchestration plan based on novel planning text generated by a generative language model. The orchestration plan may include a subset of the plurality of actions identified in the novel planning text. The computing services environment may execute the subset of the plurality of actions within the computing services environment.

A computing services environment may include application servers providing computing services including access to a database system, a unified metadata framework including autonomous agent definitions referencing action definitions defining a plurality of actions capable of being performed within the computing services environment, an agent service configured to instantiate an autonomous agent instance based on an autonomous agent definition, and an orchestration layer configured to determine an orchestration plan based on novel planning text generated by a generative language model. The orchestration plan may include a subset of the plurality of actions identified in the novel planning text. The computing services environment may execute the subset of the plurality of actions within the computing services environment.

Systems and methods disclosed herein perform privacy-preserving evaluations of artificial intelligence (AI) agents. The system identifies an auditing AI agent from a set of auditing AI agents for assessing target AI agent sets. The system obtains a data structure that defines operative boundaries for a target AI agent set and generates a reference value by applying a first transformation operation set on the data structure. The system transmits the reference value to a multi-agent storage and receives, via the multi-agent storage, a verification artifact from the target AI agent set that indicates an observed value generated by applying a second transformation operation set on an artifact set generated by the target AI agent set. The system determines, via the auditing AI agent, a verification status and responsive to a particular artifact failing to satisfy one or more assessment metrics, generates an action set to modify the target AI agent set.

A container simulation network system based on a link autonomous agent is composed of a visual interaction module, a control plane module, a network simulation module and a resource management module. The modules perform information interaction and task collaboration through a uniform interface so as to realize automatic construction and management of the simulation network, a two-layer architecture design of network bridge containers and user containers is adopted, and each user container corresponds to one network bridge container; a link autonomous agent module is deployed in the network bridge container and is used for collecting a link state, calculating a performance adaptation degree and executing a scheduling operation bit; the visual interaction module realizes visual monitoring and interaction control of a simulation state; the control plane module is responsible for simulation scene analysis, link parameter generation and global scheduling management; and the network simulation module is responsible for calling a container generation tool to generate a specific container instance and carrying out resource monitoring and adjustment on the container.

A computer-implemented method for improving workflow automation is disclosed. The method can receive a workflow including one or more processes. A process includes a plurality of tasks and links connecting the plurality of tasks. The links define an operation sequence of the plurality of tasks. The method can generate text descriptions of the one or more processes using a large language model and bind a set of tools to the workflow. The set of tools specify application programming interfaces used to perform tasks involved in the workflow. The method can create an autonomous agent configured to execute a selected task of the workflow responding to a user query. The autonomous agent identifies the selected task by comparing the user query and the text descriptions of the one or more processes. Related systems and software for implementing the method are also disclosed.

Disclosed is system for fulfilling service request using computing nodes. The system comprises a decentralized computing network, comprising computing nodes operating as autonomous agents, configured to implement software framework comprising: client-agent device 5 configured to: receive service request and generate objective therefor, and send objective to agent-device configured to send queries to a machine learning model agent and / or obtain tasks, and list of autonomous agents associated with objective; and processing arrangement configured to: generate directed acyclic graph (DAG) having 10 nodes representing first task and edges representing dependency of first task on second task(s) amongst tasks, and initialize Bloom filter of each node to track completion status of second task(s). Autonomous agent is configured to: identify second task(s), check completion status of second task(s), using Bloom filter of first task, upon completion of second 15 task(s), execute first task, and update Bloom filter.

A system and method for fail-operational mission continuity in a multi-agent autonomous system. Each autonomous agent includes an onboard Prognostic Health Management (PHM) module that monitors health using sensor data. Upon detecting an incipient fault, the PHM module calculates a prognostic Remaining Useful Life (RUL). This RUL is transformed into a quantitative Operational Risk Cost (Ω) and communicated to a multi-agent control system. The control system's dynamic task allocation algorithm uses the Ω values as key inputs in a multi-objective optimization process. This enables the system to proactively and autonomously re-allocate a task from a degrading agent to a healthy agent before a failure occurs. The degrading agent is simultaneously commanded to perform a safe contingency maneuver. This integration of real-time prognostics and multi-agent control creates a resilient, self-healing system capable of completing missions despite hardware degradation.

A computing services environment may include application servers providing computing services including access to a database system, a unified metadata framework including autonomous agent definitions referencing action definitions defining a plurality of actions capable of being performed within the computing services environment, an agent service configured to instantiate an autonomous agent instance based on an autonomous agent definition, and an orchestration layer configured to determine an orchestration plan based on novel planning text generated by a generative language model. The orchestration plan may include a subset of the plurality of actions identified in the novel planning text. The computing services environment may execute the subset of the plurality of actions within the computing services environment.

A distributed processing system for transactions of digital assets includes autonomous agents that execute off-chain. Each agent has an encapsulation of state representing at least one digital asset and is configured to process transaction requests that modify the agent state. A proof aggregation layer prevents double spending of the digital assets. A consensus layer forms a decentralized trust anchor that maintains a blockchain and certifies state transitions of the proof aggregation layer. A sending agent issues a request to certify that a particular asset state has not been previously spent and if the proof aggregation layer returns a uniqueness attestation, a recipient agent can use it to verify both correctness of the transaction execution, and validity of the uniqueness attestation. Transaction execution may take place off-chain at the agents without reliance on global consensus or shared state among all network participants.

A method for automating analysis of a plurality of wells includes receiving input data including a database related to the plurality of wells. The method also includes receiving a submission related to the plurality of wells at an autonomous agent. The method further includes performing an automated workflow for the analysis of one or more wells of the plurality of wells based on the submission using the autonomous agent. The method also includes generating an output to the submission based on the automated workflow using a writer agent of the autonomous agent. The method also includes displaying the output from the autonomous agent.

Aspects of the invention include systems and methods configured to extract enriched target-oriented common sense from grounded graphs to support efficient next step decision making of an autonomous agent. A non-limiting example computer-implemented method includes extracting common sense from a source. The extracted common sense can include a first knowledge graph. An environment state can be extracted from an observation. The extracted environment state can include a second knowledge graph. The second knowledge graph can include an interactive object and a state of the interactive object. A difference graph including the extracted common sense and the extracted environment state can be generated. A next action is selected based on the difference graph and the next action is taken by an autonomous agent.

A method includes receiving an indication of a process to be performed from a client device, identifying a first workflow associated with a first task of the process, identifying a second workflow associated with a second task of the process, initiating performance of the first and second workflows, and transmitting an indication of completion of the performance of the first and second workflows to the client device.

Systems and methods disclosed herein perform privacy-preserving evaluations of artificial intelligence (AI) agents. A first AI agent associated with a first entity obtains a machine-readable data structure defining one or more operative boundaries for a second AI agent associated with a second entity. The system generates a unique fixed reference value representing the machine-readable data structure by applying a first transformation operation set, and transmits the unique fixed reference value to a multi-agent storage to store the value. The system receives, via the multi-agent storage, a verification artifact from the second AI agent that indicates an observed value based on internal operational data of the second AI agent corresponding to the operative boundaries. The first AI agent determines a verification status of the verification artifact by comparing the unique fixed reference value with the observed value, and autonomously generates a verification record including a representation of the verification status.

Systems and methods for a transaction. Including sending a request for a service from a consumer agent to a producer agent, wherein the consumer agent and the producer agent are agents of one or more of Artificial Intelligence (AI) agents, finite state machine controlled agents, and / or graph based controller agents. Further including receiving a quote from the producer agent for completing the service. Further including providing a digital signature from the consumer agent for a digital contract, wherein the digital contract comprises terms for fulfilling the service and stipulates a payment method for the service, wherein the digital contract is signed by the producer agent. Further including recording the digital contract, the digital signature, and a financial transaction associated with the fulling of the service to a blockchain layer via a decentralized protocol.

A computing services environment may include application servers providing computing services including access to a database system, a unified metadata framework including autonomous agent definitions referencing action definitions defining a plurality of actions capable of being performed within the computing services environment, an agent service configured to instantiate an autonomous agent instance based on an autonomous agent definition, and an orchestration layer configured to determine an orchestration plan based on novel planning text generated by a generative language model. The orchestration plan may include a subset of the plurality of actions identified in the novel planning text. The computing services environment may execute the subset of the plurality of actions within the computing services environment.

Systems and methods disclosed herein perform privacy-preserving evaluations of artificial intelligence (AI) agents. The system identifies an auditing AI agent from a set of auditing AI agents for assessing target AI agent sets. The system obtains a data structure that defines operative boundaries for a target AI agent set and generates a reference value by applying a first transformation operation set on the data structure. The system transmits the reference value to a multi-agent storage and receives, via the multi-agent storage, a verification artifact from the target AI agent set that indicates an observed value generated by applying a second transformation operation set on an artifact set generated by the target AI agent set. The system determines, via the auditing AI agent, a verification status and responsive to a particular artifact failing to satisfy one or more assessment metrics, generates an action set to modify the target AI agent set.

This invention belongs to the field of artificial intelligence communication technology and discloses an AI autonomous intelligent agent execution framework architecture system based on layered decoupling. The invention integrates the core capabilities of ReAct execution loop, intelligent context compression, and autonomous error correction in the decision layer to achieve accurate parsing of instruction intent, dynamic iteration of decision logic, and autonomous error correction. The transmission layer establishes a multi-platform message intelligent routing and protocol unification mechanism to achieve efficient data interaction and instruction transmission across platforms and protocols. The execution layer integrates hybrid memory management and sandbox-isolated practical execution capabilities to achieve multi-dimensional memory of execution data, secure isolation of execution behavior, and accurate implementation of practical tasks. The system's layers are clearly defined, decoupled, independent, and collaborative, possessing high scalability, cross-platform adaptability, execution security, and decision autonomy.

A debt management and collection system and process is disclosed which analyzes input data, including, debtor information, invoice details, payment histories, and interaction logs through a recording platform. A prompt generator guides an artificial intelligence (AI) engine by converting input data into prompts. The debt management and collection system and process feature a communication platform connecting an agent coordinator with multiple AI agents. The agent coordinator analyzes debtor profiles and collection stages to develop targeted strategies, then deploys the AI agents who engage with debtors using personalized approaches. The debt management and collection system and process continuously update an input database with new interaction data, including agent actions, debtor profiles, communication records, and payment statuses.

A system and method of training a safety-critical autonomous agent. The method carried out by the system includes: obtaining initial training data to be used for training a safety-critical autonomous agent; densifying the initial training data using a data densification process in order to generate densified training data; and training a safety-critical autonomous agent using the densified training data. The data densification process includes: selecting safety-critical episodes from the initial training data in order to generate safety-critical episode training data; and / or generating artificial safety-critical episode data representing one or more artificial safety-critical episodes, wherein the artificial safety-critical episode data is generated based on at least one safety-critical episode. The densified training data is or is based on one or both of the safety-critical episode training data and the artificial safety-critical episode data.

A computer-implemented method is provided for autonomously managing tokenized assets associated with an operational venture using a blockchain protocol. The method includes deploying an agent coordination contract on a blockchain network, the contract storing on-chain incentive rules and maintaining lifecycle status and performance metrics for multiple autonomous operational agents. At least one autonomous agent is assigned to the operational venture through the contract. The agent coordination contract receives a performance report from the assigned agent, the report including operational data generated from an executed action. The contract autonomously evaluates the performance report against the on-chain incentive rules to determine a performance outcome. Based on the determined outcome, the agent coordination contract and / or an associated settlement contract autonomously updates one or more of the agent's on-chain lifecycle status, the agent's on-chain performance metrics, and a state of the tokenized assets representing the operational venture.

A computing services environment may include application servers providing computing services including access to a database system, a unified metadata framework including autonomous agent definitions referencing action definitions defining a plurality of actions capable of being performed within the computing services environment, an agent service configured to instantiate an autonomous agent instance based on an autonomous agent definition, and an orchestration layer configured to determine an orchestration plan based on novel planning text generated by a generative language model. The orchestration plan may include a subset of the plurality of actions identified in the novel planning text. The computing services environment may execute the subset of the plurality of actions within the computing services environment.

A computing services environment may include application servers providing computing services including access to a database system, a unified metadata framework including autonomous agent definitions referencing action definitions defining a plurality of actions capable of being performed within the computing services environment, an agent service configured to instantiate an autonomous agent instance based on an autonomous agent definition, and an orchestration layer configured to determine an orchestration plan based on novel planning text generated by a generative language model. The orchestration plan may include a subset of the plurality of actions identified in the novel planning text. The computing services environment may execute the subset of the plurality of actions within the computing services environment.

A system for addressing failure in an autonomous agent includes a driving subsystem, a control subsystem, a central computing subsystem, and an autonomous vehicle (AV) sensor subsystem. The system can optionally additionally include a power subsystem, a vehicle chassis subsystem, a communication subsystem, a distributed computing and / or processing subsystem, a supplementary sensor subsystem, and / or any other components. A method for addressing failure can include any or all of: detecting and responding to a failure; and operating the vehicle. Additionally or alternatively, the method 200 can include any other processes.

Systems, methods, and devices for monitoring and controlling communications between autonomous agents are disclosed. The system monitors real-time communications between autonomous agents, intercepting and recording each communication. Communications are translated to a standardized language and processed through communication protocol filters that evaluate compliance with predefined operational policies. The system parses each translated communication to identify policy violations. When violations are detected, the system modifies communications to ensure compliance with operational policies. All communications and modifications are recorded via distributed ledger technology for audit and accountability purposes. This approach enables comprehensive oversight of autonomous agent interactions while maintaining tamper-proof records of all monitoring and control activities.