39 results about "Software agent" patented technology

The governed interaction interface maintains an identity-preserving semantic-state for a knowledge entity and updates it only through validated semantic evidence generated autonomously by execution mechanisms. Semantic intentions describe semantic needs and are transformed into capability-requests containing no operational commands. Execution mechanisms—including environmental devices, perception models, symbolic analyzers, virtual actors, and software agents—interpret capability-requests independently through tool-side semantic interpreters and may act or decline to act. The system does not observe or evaluate tool behavior and receives only semantic evidence describing semantic meaning of any resulting effect. The governance engine evaluates each evidence fragment independently under identity, coherence, lineage, evidentiary sufficiency, deviation constraints, and contextual compatibility. Semantic-state transitions occur only when validated evidence satisfies governance constraints. The system performs no prediction, optimization, control computation, multimodal fusion, or supervisory coordination, remaining fully separated from device-level behavior.

The Universal Transportation Operating System (UniTOS) is an autonomous cyber-physical operating system that coordinates all movable Assets—machines, containers, vehicles, and software agents—across every Domain of human and machine activity. UniTOS integrates three core services: the Process Layout Asset Navigation Tool (PLANT) for PLAN authoring and systemic learning, the PLAN Execution Tool (PLANET) for Asset-level execution and variance reporting, and the Monitor-Manage-Maintain (M3) service for Domain-level coordination and variance reconciliation.

Systems and methods described herein provide a computer-implemented method for process simulation using a multi-agent system. A software agent is trained using historical process data associated with a process. Each software agent represents a single task in the process. Based on the candidate process model, the process is simulated by executing the multi-agent system to generate simulation results. The software agent operates autonomously within the multi-agent system based on the trained behavior. The process is also performed using a runtime configuration based on the candidate process model. Execution of the process generates runtime results for comparison with the simulation results. In some examples, the candidate process model is adjusted based on the comparison, and simulation and execution of the process are repeated using the adjusted multi-agent system and the adjusted runtime configuration, respectively. A deployment process model is generated based on the adjusted candidate process model.

The present disclosure is directed to systems and methods directed to improving the functions of a vehicle. Systems and methods are provided that provide a custom tool that autogenerates a set of software agents that allows a system to separate processing, transmission and receiving of messages to achieve better synchronization. The disclosure herein also provides a simplified method of key provisioning by designating one client as a server and assigning a symmetric key to every other client permanently provisioned between that client and the server. Systems and method are further provided that predict faults in a vehicle. Systems and methods are also provided that preserve data in the event of a system crash. Systems and methods are also provided in which an operating system of a vehicle detects the presence of a new peripheral and pulls the related interface file for that new peripheral. Further, a data synchronization solution is provided herein which provides optimized levels of synchronization.

This invention discloses a training-free method for improving GUI localization capabilities based on an operation chain, relating to the fields of human-computer interaction and intelligent software agent technology. The method includes: acquiring a target interface image and natural language commands; obtaining initial candidate regions through a basic localization model; performing local cropping followed by secondary prediction and mapping back to the original image to update the region; applying a dynamic mask to the image and repeatedly predicting to generate spatially mutually exclusive candidate boxes; constructing a labeled comparison image; combining the input error correction model with commands and rule-based prompts; and selecting the optimal candidate box as the final localization result. This invention significantly reduces accuracy and ambiguity biases in localization by performing a series of interpretable inference time-series operations on the input screenshot and natural language commands, thereby improving the executable localization capabilities and stability of desktop intelligent agents on edge devices such as computers and mobile phones.

Embodiments of the invention are directed to systems, methods, and computer program products for provisioning a virtual lab environment for software development. In some embodiments, the method includes defining a set of features in the virtual lab environment; receiving, via a user input on a user interface, an unstructured dataset; generating a structured dataset using a generative artificial intelligence (AI) engine, where the unstructured dataset is an input of the generative AI engine; identifying, based on the structured dataset, a preferred configuration, where the preferred configuration comprises a target set of features; initiating a code delivery process, where the code delivery process includes configuring the set of features in the virtual lab environment to match the target set of features. The method may also include identifying at least one available software agent and displaying the at least one available software agent on the user interface.

A processor circuit is configured to receive, while a current software agent is executing in a current execution mode, an indication of an execution mode transition that attempts to change an execution mode index from a current value indicative of the current execution mode to a new value indicative of a new execution mode. The processor circuit is configured to access, based on the current privilege level, particular execution mode transition information in a storage circuit to determine whether the execution mode transition is allowed. The processor circuit is configured to determine, based on particular execution mode transition information, whether to update the current value indicative of the current execution mode. The processor is further configured to update the current value indicative of the current execution mode based on a determination that the execution mode transition is permitted.

A method for the automated configuration of software systems involves processing a configuration request from multiple software agents, each of which has a large language model. Each agent contributes to fulfilling the request based on its role and expertise (domain expert, application expert, configuration expert). The result is a new or adapted configuration of the software system.

In some embodiments, the present disclosure provides an exemplary method that may include steps of identifying at least one computing specification image within a plurality of computing specification images; monitoring each data agent within the plurality of preinstalled data agents for a predetermined period of time to establish a data agent usage baseline associated with each data agent within the plurality of preinstalled data agents; utilizing a chaos engineering algorithm to dynamically perturb each data agent; calculating a usage test score for each data agent within the plurality of preinstalled data agents; calculating an overall data agent-specific usage score associated with each data agent within the plurality of preinstalled data agents based on the plurality of data agent-specific usage test scores; and rejecting at least one data agent within the plurality of preinstalled data agents from being utilized to launch the instance of the software application.

System and methods for computer modeling in medicine. A sort of period table of medical models is described for personalized diagnostics, prognostics and therapeutics, including at least 80 major categories of medical models. Generative artificial intelligence and geometric deep learning techniques, and algorithms including 2D and 3D graph machine learning and GenAI algorithms, are described, tailored and applied to diagnostic disease description, prognostic prediction and therapeutic development and management, including generation of novel synthetic drugs. The AI and machine learning techniques and algorithms are applied to understand each individual's genetic, RNA and protein anomalies that represent the source of many unique patient diseases. AI-enabled software agents assist physicians and researchers in building patient medical models. Several personalized medicine applications of individualized medical modeling include cardiovascular

Disclosed herein are embodiments for managing a virtual reality (VR) training exercise via a management server. The management server outputs a graphical dashboard including one or more skill nodes, and selects one or more software agents associated with the skill nodes. The management server provides the software agents to at least one host computing system communicatively coupled to a near-to-eye display device. The near-to-eye display device is configured to display a virtual three dimensional (3D) training environment including a plurality of interactive 3D virtual objects. The software agents are configured to collect VR observables data while the trainee performs actions within the virtual 3D training environment. Based on the VR observables data collected, the management server determines that one or more skills have been demonstrated during the training exercise, and updates the one or more skill nodes to graphically indicate the one or more skills demonstrated by the trainee.

A software agent is installed on each endpoint device within a plurality of endpoint devices. Each software agent manages a unique endpoint device. Each software agent is communicatively coupled to an orchestration software component. The software agents monitor security activities on each endpoint device and send security information details on each endpoint device to the orchestration software. The orchestration software generates security categories and a compliance score in each category for each endpoint device. The orchestration software creates a proactive security score (PSS) for each endpoint device, based on the security information compliance scores. The orchestration software generates a global proactive security score (GPSS) based on the average PSS for the plurality of endpoint devices. The orchestration software reports the PSS and GPSS for the plurality of endpoint devices.

Methods and control devices for providing functionality in a vehicle. The present invention relates to a method for providing functionality in a vehicle, particularly a software-defined vehicle (SDV), wherein at least two software modules, particularly two software agents, are executed on a control device, characterized in that the at least two software modules are distinct from each other, and each of the at least two software modules provides the functionality through a separate communication interface.

Method for the automated coordination of a maintenance process for a motor vehicle, characterized by the following features: - Electronic reception of technical diagnostic data representing the condition of vehicle components via a data interface, - Semantic analysis of the received diagnostic data using a software agent based on a large language model, whereby the language model automatically derives a specific maintenance requirement and a list of spare parts required for maintenance as a machine-readable instruction from the technical diagnostic data, - Automated sending of electronic queries to external computer systems of workshops and spare parts suppliers using the derived instructions for determining workshop capacities and spare parts availability in real time, - Calculating an optimized maintenance appointment by algorithmically comparing the derived maintenance requirements with the determined workshop capacities and spare parts availability.

Systems and methods described herein provide a computer-implemented approach for process simulations using multi-agent systems. Software agents are trained using historical process data associated with a process. Each software agent represents a single task in the process. Based on a candidate process model, the process is simulated to generate simulation results by executing a multi-agent system. The software agents operate autonomously within the multi-agent system based on trained behavior. The process is also executed using a runtime configuration that is based on the candidate process model. The execution of the process generates runtime results for comparison with the simulation results. In some examples, the candidate process model is adjusted based on the comparison, and the simulation and the execution of the process are repeated using an adjusted multi-agent system and an adjusted runtime configuration, respectively. A deployment process model is generated based on the adjusted candidate process model.

A system and method for failover for cloud-native applications, such as cloud-native video-conferencing services, that includes a software agent that monitors the health of services executing on servers. An agent monitors predefined metrics of a service and sends alerts to a plan-execution system when a monitored metric fails to satisfy a predefined condition. The plan-execution system applies predefined rules to received alerts to determine whether a service is failing. The plan-execution system instructs a command center to redirect client requests for a failing service to a failover service.

The invention relates to a test system (10) comprising a test device (12) for acquiring data (16) characterizing a vehicle function (14) of a motor vehicle and a storage device (18) for storing the acquired data (16), wherein a software agent (22) is receivable at an interface (20) of the test device (12) and is executable by means of an electronic computing device (24) of the test device (12), and the software agent (22) is configured to process the acquired data (16) on the test device (12), wherein a result (26) of the processing is available at the interface (20). The invention further relates to a method for operating a test system (10), a computer program, and an electronically readable data carrier.

Systems and methods are provided that may be implemented to orchestrate trusted enrollment of an endpoint client information handling system by deploying a signed payload of an enrollment package to the endpoint client system, and by using a client software agent executing on the endpoint client system to first verify the distribution chain and / or signature of the deployed enrollment package before proceeding to use other information contained in the enrollment package to contact a registration server to enroll the endpoint client system.

The invention relates to a method for providing functionality in a vehicle, in particular a software defined vehicle (SDV), wherein at least two software modules, in particular two software agents, are executed on a control unit, characterized in that the at least two software modules differ from each other and each of the at least two software modules provides the functionality via a separate communication interface.

A user of an identity management system may configure a software agent with a set of parameters within one or more user interfaces of an agent management service. The set of parameters may include an identifier of an application programming interface (API) endpoint of a first service that the software agent is authorized to query and one or more permissions associated with queries to the API endpoint by the software agent. Further, the user may receive an authentication token for the software agent from the agent management service. The software agent may use the authentication token for accessing resources of the service via the API endpoint in accordance with the one or more permissions. Thus, the user may configure the first software agent with the authentication token to enable the software agent to perform the queries to the API endpoint of the first service.

A distributed indexing and resolution architecture is disclosed for decentralized systems requiring modular, trust-scoped mutation control and dynamic alias governance. The system comprises a plurality of index entries arranged in a parent-child hierarchy, each associated with a structured alias and governed by one or more anchor nodes. Anchors perform localized resolution, mutation validation, and restructuring operations under deterministic policy constraints, enabling semantic scope enforcement and entropy-sensitive adaptation without requiring global consensus or centralized control. The architecture supports scoped alias traversal, asynchronous mutation proposals, and elastic anchor registration based on system state metrics. The indexing substrate may be integrated into heterogeneous infrastructures, including systems comprising distributed software agents, semantic execution platforms, or pseudonymous identity frameworks. Anchors coordinate within defined trust domains to ensure lineage continuity, dynamic rekeying, and semantic integrity across independently governed segments of a decentralized namespace.

A method, including collecting, by a security server, reports from multiple computing devices of events belonging to a set of specified event types occurring in execution of software processes on the devices, and collating the reports in the server to extract context information with respect to each of the events. Upon detecting an event occurring in execution of a process on a given device and matching one of the types, a software agent executing on the given device extracts, one or more features from the detected event, and conveys a query with respect to the detected event from the agent to the server. Upon receiving, from the server in response to the query, the context information with respect to the detected event, the agent decides to initiate a protective action on the given device based on the received context information and the one or more features extracted by the agent.

Systems and techniques for facilitating unified multichannel communication are provided. The described systems and techniques improve communication technology through an encompassing, channel-agnostic approach which unifies disparate communication modes into a singular coherent thread. A unified multichannel communication (“UMC”) service of a UMC platform can initialize a UMC thread for a UMC session, where the UMC thread can be used to facilitate unified multichannel communication. The UMC session can involve multiple participants, including human users and software agents (e.g., conversational bots, virtual agents, digital assistants, and other dialog interfaces). The UMC platform can facilitate creating and interacting with a digital assistant providing unified multichannel communication.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for using conversation histories to augment a software agent. In particular, the software agent can selectively and adaptively be provided with data from conversation history data that comprises respective segment data for each of one or more past segments of each of a plurality of past conversations between a user and a software agent, the respective segment data comprising a respective segment embedding for the past segment.

A method for automatically configuring a software system. In this case, the configuration request is processed by a plurality of software agents, each agent having a large language model (LLM). Each agent contributes to completion requests based on its role and professional knowledge (domain experts, application experts, configuration experts). The result is a new or adapted configuration of the software system.

A control application generates log files that provide information about the management of multiple devices it is responsible for. The information in the log files depends on messages received from the devices or commands issued to the devices. For example, in the case of a smart meter, the generated log files may include meter readings, firmware changes, firmware updates, instructions on whether the meter is open or not, and instructions for overheating in the meter. A software agent extracts information from the log files that can be analyzed in order to determine anomalies that may be related to an attack on the system. The analysis performed may include pattern matching of the information obtained from the log files, performing AI analysis of the information obtained from the log files, and identifying signatures.

The application discloses a computer software daemon method and system, which uniformly sets a start sequence and an administrator password of a basic input / output system (BIOS) of a computer. When the computer starts, the BIOS detects an operating system version and a basic software agent (miniagent) of the computer, and the miniagent is recovered when the miniagent is abnormal. After the operating system of the computer starts, the miniagent detects daemon software and data, and the abnormal software and data are recovered to a running state, and the software daemon is suitable for scenes such as reinstallation of an operating system, replacement of an operating system, storage space formatting, replacement of a hard disk storage medium and the like.

The invention provides an operation and maintenance method of a software agent and an operation and maintenance system of the software agent, which can be applied to the technical field of networks. The operation and maintenance method of the software agent comprises the following steps: a network operation and maintenance service node responds to and receives a first request object related to Agent operation and maintenance, and analyzes the first request object to judge whether the request object meets a compliance requirement or not, so that the accuracy and compliance of an operation and maintenance process are ensured. And under the condition of determining that the first request object meets the compliance requirement, the network operation and maintenance service node determines and sends a second request object to the network controller. And the network controller executes the target operation and maintenance operation on the target computing node and / or the target software agent according to the type of the operation and maintenance operation in the second request object. According to the scheme provided by the embodiment of the invention, a large number of software agents can be efficiently managed, and furthermore, the stability and the security of a network can be ensured.

The present disclosure relates to systems and methods aimed at improving vehicle functionality. Systems and methods are provided that provide a customization tool that automatically generates a set of software agents that allow the system to separate the handling, transmission, and reception of messages for better synchronization. The disclosure herein also provides a simplified method of key configuration by designating one client as a server and assigning symmetric keys for each other client that is permanently set between the client and the server. Systems and methods are also provided that predict failures in a vehicle. Systems and methods are also provided that preserve data in the event of a system crash. Systems and methods are also provided in which the operating system of a vehicle detects the presence of a new peripheral device and pulls the relevant interface file for the new peripheral device. Furthermore, a data synchronization solution is provided herein that provides a level of synchronization that is optimized.

With the development of automation and intelligent technologies, various systems often contain multiple entities capable of autonomous decision-making (such as industrial robots, IoT devices, vehicle control units, and software agents). These entities need to collaborate to complete complex tasks, avoid conflicts, improve efficiency, and optimize resource utilization. However, existing technologies suffer from drawbacks such as decision-making conflicts, limited collaboration methods, lack of adaptive learning, and poor cross-domain applicability. Therefore, a general collaborative decision-making method is needed that can flexibly coordinate the decision-making intentions of multiple entities, dynamically select collaborative strategies, and possess learning capabilities. This application provides a multi-entity collaborative decision-making method, system, and computer-readable storage medium, aiming to enable multiple entities to dynamically select collaborative strategies based on various factors, resolve conflicts through negotiation, and continuously optimize from feedback, making it widely applicable to various multi-entity collaborative scenarios.