1276 results about "Intelligent agent" patented technology

Systems and methods are provided for enabling search and query functions. A query system having a framework, executed on one or more processors, includes a plurality of Artificial Intelligence (AI) agents working to support one of text-to-Structured Query Language (SQL) or text-to-Python, wherein the plurality of AI agents include a first AI agent prompted to act as a research analyst for performing a task of interpreting a natural language query from a user, wherein the natural language query relates to natural language to the one of text-to-SQL or text-to-Python; a second AI agent prompted to act as a search data engineer for performing a task of executing a search based on the natural language query; and a third AI agent prompted to act as a code developer for performing a task of writing code based on the search, wherein the plurality of AI agents act autonomously yet collaboratively.

This application applies to the field of intelligent agents, providing a medical intelligent agent system, a medical system, a medical system architecture, and an application method. The medical intelligent agent system includes: an intelligent agent platform for generating and / or editing intelligent agents based on input information; and a transmission unit for exporting intelligent agents to the medical system for execution, and / or importing intelligent agents from the medical system for editing. Using this medical intelligent agent system can improve the efficiency of intelligent agent generation and ensure that the clinical data required for the generated intelligent agents to run in the medical system does not need to be externally transmitted, thus improving the security and privacy of clinical data.

This invention discloses an adaptive adjustment method for intelligent display equipment used in digital exhibitions, specifically relating to the field of digital exhibition technology. The method involves collecting multi-source data such as ambient light, visitor distribution, and sound through distributed lightweight sensor nodes; performing semantic fusion using a lightweight neural network to construct a dynamic exhibition hall context graph; instantiating an intelligent agent for each display device; generating resource scheduling proposals based on a shared reward mechanism and a multi-agent collaborative decision-making algorithm; an arbitrator detecting and resolving resource competition and effect offsetting conflicts; outputting a globally consistent set of control instructions; ensuring smooth execution of instructions by the devices; dynamically generating adapted display content based on contextual semantics; and continuously optimizing the decision-making model through online learning based on visitor behavior feedback. This invention achieves collaborative scheduling of equipment resources and adaptive content generation, improving the exhibition experience and resource utilization efficiency.

This invention relates to the field of training data construction technology, and discloses a method, system, terminal, and storage medium for generating intelligent agent training data based on high-fidelity dynamic interactive assets. The method includes: constructing a high-fidelity simulated scene and establishing a decoupled structure between the interactive assets, the visual representation layer, and the physical proxy layer; loading a high-fidelity virtual human as the interactive demonstration subject in the scene; parsing and planning natural language tasks to generate a structured sub-task sequence, and completing instantiation mapping in conjunction with the interactive assets; performing physical simulation based on the action sequence, collecting multimodal observation data and object state changes, and aligning multi-dimensional data under a unified time reference to form dynamic interactive assets and high-reliability training data. This invention achieves the unification of high-fidelity rendering and physically consistent interaction, and can automatically generate replayable, searchable, and combinable dynamic interactive data, thereby significantly improving data generation efficiency, realism, and cross-scene transfer capabilities.

This invention belongs to the field of intelligent agent large language model service technology, and discloses a chip computing system, device and application for intelligent agent large language model. Through the collaborative design of hardware architecture and software scheduling, it systematically solves the core technical challenges faced by intelligent agent large language model services. Specifically, it includes a hardware and software collaborative implementation scheme for resource partitioning, key-value cache management and runtime scheduling of pre-filling, decoding and tool call related workloads in a multi-chip encapsulation and inconsistent memory access environment.

The present application discloses a method and device for constructing a digital power system based on multifunctional intelligent agents. The method comprises: respectively extracting feature production element data and control production element data from power data of a power plant side and power data of a power grid side; constructing a target data vector on the basis of a power function requirement, and determining key control production element data associated with the power function requirement; using an artificial intelligence algorithm to learn a mapping function between the target data vector and the key control production element data, constructing a functional operator using the mapping function as a core, and constructing an intelligent agent on the basis of the functional operator; and adding intelligent agents corresponding to a plurality of different power function requirements into a digital power system as power function implementation units. The system can realize data-driven diversified and digital power functions, and implement more accurate capturing of the relationship between data, thereby forming high-value data assets in the power system.

This invention discloses an intelligent alarm and control method for personnel safety in power plants, relating to the field of power industry safety control technology. The method includes: acquiring multimodal sensing data related to personnel based on the existing sensing system of the power plant; using a multimodal analysis model to fuse and analyze the collected multimodal sensing data to identify personnel safety risks; generating an alarm trigger signal when the risk level reaches a preset threshold; combining intelligent agent technology to generate a personalized alarm strategy after receiving the alarm trigger signal, simultaneously finding the nearest alarm device based on the real-time location of the personnel for continuous alarm, and establishing a continuous monitoring mechanism to track personnel status in real time; continuously monitoring the behavior and location changes of the alarmed personnel until the risk is confirmed to be completely eliminated. This invention enables cross-system correlation analysis, improves the accuracy of risk identification, effectively shortens response time, and improves the safety level of power plants.

The application relates to a knowledge-driven multi-agent cooperative reactor scheme demonstration system and a design method, medium and equipment thereof, the system comprising: a knowledge internalization unit for converting unstructured and semi-structured documents into a dynamic knowledge source which can be queried and utilized by a model in real time; a knowledge structuring unit for extracting core entities, relationships and attributes from the knowledge source and constructing a professional knowledge graph of a reactor design field; and a knowledge application unit for constructing intelligent agents and a collaborative working mechanism of multi-professional intelligent agents based on the knowledge source and the knowledge graph, and constructing an intelligent question and answer interface. Through automatic knowledge management and intelligent agent collaborative work, the application significantly reduces the time and effort of manual intervention and improves the efficiency of reactor scheme demonstration.

The application discloses a kind of computing power network green space-time task scheduling and mixed energy collaborative optimization method.The steps are as follows: one, establish the computing power network system model of fusing computing resources, network routing resources and mixed energy, construct multi-objective joint optimization problem;Two, model the problem as a Markov decision process, define the state space containing task, network and energy state, and the action space composed of computing power node selection, routing path selection and forwarding time;Three, use the integrated deep reinforcement learning framework, configure multiple intelligent agents with different preference weights for parallel training, to achieve the best balance between quality of service and carbon emissions;Four, according to the integrated strategy of complete training, combined with the real-time input task flow and carbon emission intensity, output the optimal space-time scheduling decision and energy storage charging and discharging strategy.

Systems and methods for natural disaster damage analysis. Aerial images are converted (710) into a set of property images. The property images are then clustered (720) using vector embedding. Clustering the property images includes classifying the property images into separate categories, determining a symmetric similarity between the property images in each category, and clustering the property images based on the similarity. A first artificial intelligence agent extracts (730) damage information from a set of representative members of the clustered property images, where the damage information includes damage level information and damage reasoning information. The damage information is then stored (740) in a datastore with at least two databases, where at least one of the databases stores damage reasoning information and at least one other one of the databases stores damage level information.

The utility model provides a kind of fresh seafood transportation intelligence, including transport cabin, supply unit, the supply unit is used to provide clean water and oxygen to transport cabin, the supply unit includes mixing cylinder, the mixing cylinder two sides are provided with water storage tank and oxygen storage tank respectively, the water storage tank and oxygen storage tank are connected with mixing cylinder by feeding assembly, the mixing cylinder is connected with transport cabin by pumping component;Mixing assembly is provided in the mixing cylinder, and the mixing assembly is used to mix the substance in the mixing cylinder.The utility model utilizes mixing cylinder, feeding assembly and pumping component and other structures can send clean water into transport cabin, and utilize mixing assembly can mix the water body in the mixing cylinder, and cooperate temperature control component can deliver different oxygen content, temperature water body into transport cabin, can satisfy the survival needs of different seafood, ensure the survival rate of seafood in the process of transportation, reduce the cost of seafood transportation.

The application discloses a Text-to-SQL intelligent agent coordination system and method for perceiving potential intention of a user in a multi-round context. The system comprises a memory bank, a prompt strategy pool, a strategy recommender, an SQL generator, an SQL refiner and a strategy optimizer. The memory bank is used for storing system running data. The prompt strategy pool is used for storing prompt strategies. The strategy recommender is used for receiving user information and strategy information of the prompt strategies, identifying the current potential intention of the user based on the user information and the strategy information, and matching the optimal strategy from the prompt strategy pool according to the potential intention to constrain the generation of an SQL query statement. The SQL generator generates an SQL query statement based on the current natural language query of the user, the system running data and the optimal strategy. The SQL refiner is used for adjusting and iteratively updating the SQL query statement. The strategy optimizer is used for updating the prompt strategies. The application increases strategy selection before SQL generation, so that the SQL generator can generate an SQL statement meeting the user demand at one time with a higher probability, and the cost is reduced.

The present application relates to the technical field of vehicle automatic driving, in particular to a kind of intelligent Agent trajectory planning control method and system based on HDMap;The method mainly includes four steps of the initialization of vehicle Agent, formal path query, entry mode confirmation and automatic driving according to path;High-precision semantic map and the idea of intelligent Agent are used in the present scheme, and a kind of vehicle Agent implementation scheme for flexible operation along lane is presented;In the entry mode of vehicle Agent, the present scheme designs a kind of ingenious vehicle Agent entry mode from the angle of time and space;The present scheme utilizes lane center line segment information in map, regulates the motion trajectory of vehicle, and provides flexible acceleration setting interface, so that the speed of vehicle Agent can change in real time according to the demand of user or traffic condition while automatically driving along lane, which reserves interface for the access of subsequent vehicle anti-collision strategy.

An information processing method is executed by a computer in a system incidental to a room. An Artificial Intelligence (AI) agent includes a room AI agent and personal AI agents. The room AI agent receives and responds to an instruction from a user in the room via a voice interaction interface (VUI). The personal AI agents correspond to users in the room. The information processing method includes connecting each AI agent to a virtual space enabling interaction with each other. The room AI agent recognizes the user in the room and a topic of a proposal request from the user via the VUI and notifies the topic and personal AI agents of the recognized user. The personal AI agents generate one or more proposals based on the topic and user's profile. The computer applies, to the system, a setting or processing corresponding to a proposal adopted by the user.

This invention discloses a fuel cell hybrid propulsion system and its power fluctuation-consumption synergistic optimization method. The system includes a fuel cell power generation unit, a lithium-ion battery unit, an electric drive unit, a sensing and data acquisition unit, and an energy management controller. Based on near-end strategy optimization, an intelligent agent is constructed with system state and operating condition information as input and power source power allocation commands as output. A reward function integrating total energy consumption penalty and power fluctuation penalty is designed to drive the intelligent agent to learn the optimal energy management strategy in a continuous action space. This invention can suppress frequent and drastic fluctuations in lithium-ion battery power, extend battery life, ensure system safety, and minimize overall hydrogen fuel consumption while meeting dynamic power demand and safety constraints. It achieves synergistic optimization of long-term operational economy and system output stability, enabling efficient, smooth, and long-life operation of the hybrid propulsion system in dynamic environments.

Systems and methods are described for comparing execution of two or more artificial intelligence (AI) AI agents. A platform can provide a user interface (UI) that allows for selection or creation of multiple AI agents. The AI agents can utilize different agent objects, such as different prompts, datasets, or models. The AI agents can be displayed on a single UI screen, where execution of the AI agents is simultaneously simulated. The same inputs can be provided to the multiple AI agents, and the corresponding outputs can display on screen. The platform can also vectorize and compare the semantic similarity of the outputs, presenting an indicating of the semantic similarity on the same UI screen.

This invention discloses a multi-source data intelligent connection management method, belonging to the field of data processing and information fusion technology. The method includes: deploying an intelligent agent program to listen to window message streams and reconstruct operation paths; synchronously capturing and parsing network requests to obtain structured business data; establishing a mapping relationship between operations and data through multimodal fusion parsing; filtering target data based on a no-code rule base; standardizing formats using a conversion engine; generating RPA instructions with the assistance of a large model; embedding a digital credential mechanism throughout the entire chain to ensure data integrity; and dynamically enhancing business logic through extension point injection. This invention aims to solve the problems of difficult data collaboration, high adaptation costs, and insufficient security caused by the lack of standard interfaces in heterogeneous business systems. It achieves high-precision, low-latency, and auditable automatic data collection, conversion, and entry across closed systems, significantly shortening the supplier access cycle and improving the efficiency of supply chain four-flow collaboration and system scalability.

The application discloses a financial risk control report generation method, device, equipment, storage medium and product, relates to the technical field of artificial intelligence, and the method comprises the following steps: generating a preference data set through a supervised fine-tuning technology, a preset risk control report corpus and a preset large language model; performing iterative preference training on the preset large language model according to the preference data set; and generating a financial risk control report through a large language model after training and an intelligent agent-based retrieval enhancement generation technology. The application uses the risk control report corpus of a user to generate a preference data set through supervised fine-tuning, a corpus and a large language model, thereby reducing the dependence on a large amount of labeled data; the model is trained through the preference data set, a database query mode is provided to improve the report generation efficiency of the model, thereby solving the problem that a large number of high-quality samples are required for training in the prior art, and only a small number of samples and iteration times are required to align the output of the large language model with the expected behavior of the user.

Systems and methods for natural disaster damage analysis. Aerial images are converted into a set of property images. The property images are then clustered using vector embedding. Clustering the property images includes classifying the property images into separate categories, determining a symmetric similarity between the property images in each category, and clustering the property images based on the similarity. A first artificial intelligence agent extracts damage information from a set of representative members of the clustered property images, where the damage information includes damage level information and damage reasoning information. The damage information is then stored in a datastore with at least two databases, where at least one of the databases stores damage reasoning information and at least one other one of the databases stores damage level information.

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.

This application relates to the field of intelligent aerospace technology and discloses a satellite autonomy method driven by embodied intelligent agents, applicable to subsatellites belonging to an in-orbit constellation. It constructs a multi-agent framework comprising multiple autonomous intelligent agents, including at least a resource assessment agent and a resource optimization agent. In response to a resource assessment command regarding the target mission, the method acquires the subsatellite's in-orbit operating parameters. The resource assessment agent is invoked to perform resource assessment based on the in-orbit operating parameters, obtaining the mission resource assessment result, which is then fed back to the in-orbit constellation. If mission feasibility indicates that the subsatellite can execute the target mission, the method acquires a single-satellite mission plan fed back by the in-orbit constellation. The resource optimization agent is invoked to optimize resource allocation based on the single-satellite mission plan, obtaining a mission operation plan. Its beneficial effects are that it improves the intelligence level of subsatellites in remote sensing observation missions and enhances the satellite's in-orbit autonomy.

This application discloses a security detection method, apparatus, device, storage medium, and computer program product, relating to the field of artificial intelligence technology. The method includes: isolating a modified function file and sending the modified function file to the cloud for security detection; responding to a function installation request, determining a target function file based on the request, and installing the function based on the target function file; and deleting the isolated modified function file upon completion of installation. Because it can quickly isolate files and transmit them to the cloud for security detection when changes are detected in the function files corresponding to local intelligent agent functions, and then install the function using the file downloaded from the cloud after security detection, it ensures rapid detection of local file changes while preventing local installation and ensuring that all installations are judged by the cloud, thus improving security.

This application relates to a method, system, execution method, and medium for constructing an intelligent agent workflow based on heterogeneous node collaboration, and relates to the field of intelligent agent construction and execution technology. The intelligent agent workflow construction method includes: parsing task scenario requirements, matching and selecting task application nodes in conjunction with a preset standard node library, and marking unresolved elements; arranging task application nodes according to the task execution flow, and constructing a task flow node skeleton in conjunction with node-specific parameters; verifying and filtering unresolved elements, and correcting and filling the task flow node skeleton in conjunction with business logic to generate a visual workflow diagram; in the construction phase, by parsing task requirements, matching application nodes from the standard node library and marking unresolved elements, arranging the node skeleton according to the business flow, and constructing a visual workflow in conjunction with specific parameters; in the execution phase, generating task sequence codes and allocating resources according to node dependencies, determining the anomaly level by real-time monitoring of node running status, and correcting abnormal flows.

1. Name of the product in this design: Interactive information and operation button display area of ​​a voice-interactive graphical user interface for electronic devices. 2. Purpose of this design: An electronic device. 3. The key design features of this product are the graphical user interface in the electronic device for which protection is sought. 4. The image or photograph that best illustrates the key design points: Design 1 change state diagram. 5. Design 1 is designated as the basic design. 6. Purpose of Graphical User Interface: The graphical user interface is used for voice interaction, such as voice interaction with an intelligent agent. The part of the graphical user interface that needs protection is the interactive information and operation button display area of ​​the voice interaction graphical user interface. 7. Human-computer interaction method of graphical user interface: In Design 1, the user clicks the voice input button in the main view of Design 1, and the graphical user interface changes from the main view of Design 1 to the change state diagram of Design 1 to display the user's voice input status and the information of the recognized user voice input. In Design 2, when the user clicks the voice input button in the main view of Design 2, the graphical user interface changes from the main view of Design 2 to Design 2 Change State Figure 1 to display the user's voice input status and the recognized user voice input information. When the user slides up in Design 2 Change State Figure 1, the graphical user interface changes from Design 2 Change State Figure 1 to Design 2 Change State Figure 2 to display a prompt message to cancel sending voice. 8. Other situations requiring explanation: The portion of the graphical user interface shown by the dashed lines in the views of Design 1 to Design 2 does not constitute the part that is protected by this design.

The application provides a control method and system of a smart home appliance, and relates to the technical field of large language models, which comprises the following steps: in response to receiving a control request sent by a user terminal, extracting a user identifier carried by the control request; if the user of the user identifier is verified as a legal user, calling an intelligent agent configured by the smart home appliance to analyze the control request to obtain a user intention and at least one target home appliance; querying model information corresponding to the target home appliance; inputting the model information and the user intention into a preset large language model, outputting a device control instruction corresponding to each target home appliance by the large language model, and sending the device control instruction to the target home appliance to control the target home appliance. The control method and system of the smart home appliance can effectively reduce the risk of illegal control of the smart home appliance, thereby improving the security and stability of the entire control system.