812 results about "Task management" patented technology

Systems, methods, and software are disclosed herein for a system of agents for managing tasks of software applications which is guided by generative AI. In an implementation, a computing apparatus determines that a task has been assigned to an application assistant of an application. The application assistant includes multiple agents which interact with a generative AI model. The computing apparatus orchestrates the multiple agents in their interactions with the generative AI model in furtherance of completing the task and updates the contextual information of the task based on the interactions.

The invention relates to the technical field of robot scheduling, and discloses a robot task management framework system based on asynchronous communication. The system comprises a task asynchronous analysis module for performing time sequence decoupling on an original task instruction stream of a heterogeneous robot terminal by means of a multi-channel buffer queue to separate out independent executable task units; the resource dynamic mapping module is used for establishing a variable granularity resource allocation mapping table according to cluster real-time load and task resource requirements, and recording various resource dynamic binding relationships; the task priority reconstruction module is used for constructing a directed acyclic graph scheduling topology based on task logic dependence and deadline constraint, and generating a weighted execution sequence through topological sorting; the exception isolation processing module captures exceptions during operation and triggers an isolation strategy; and the cross-node cooperation module guarantees the multi-robot cooperation task state consensus through a distributed consistency protocol. The system is suitable for heterogeneous robot cluster complex task scenes.

The invention provides a timed task execution optimization method and system, and aims to solve the problems of inflexible static priority scheduling, unintelligent resource allocation and the like in the prior art. According to the method, a distributed timed task intelligent scheduling framework is constructed and comprises five core components including a task management console, a scheduling decision engine, a resource monitoring agent, a task execution cluster and metadata storage. Task basic information is obtained through task feature extraction, a dynamic priority score is calculated based on decision factors such as SLA urgency, resource matching degree and service weight, and task priority ranking is achieved. And performing intelligent task allocation by adopting a BestFit algorithm, and allocating the task to the optimal execution node. The system monitors the CPU utilization rate, the memory occupation and the IO waiting time of the nodes in real time, and when the CPU utilization rate exceeds 85%, an elastic resource allocation strategy is triggered. And when the task execution time exceeds the pre-estimated duration, performing task splitting and rescheduling based on a dynamic fragmentation algorithm.

The present application relates to the technical field of large-scale data processing, and particularly relates to a parallel computing method and system suitable for large-scale data processing. The system comprises a task management unit, a distributed load balancing module, an elastic expansion architecture, an intelligent communication optimization module, and a resource monitoring unit, wherein the task management unit divides large-scale data into a plurality of sub-tasks by means of a task decomposer, and distributes the sub-tasks to computing nodes by means of a task scheduler and a priority distributor; the distributed load balancing module achieves global load balancing by means of a load sensing unit, a dynamic adjustment unit and a balance optimization unit; the elastic expansion architecture dynamically adjusts system resources by means of a node manager, a resource pool controller and an expansion decision-making device; the intelligent communication optimization module optimizes inter-node communication by means of a communication path planning unit, a bandwidth distribution unit and a delay compensation unit; and the resource monitoring unit monitors the system performance in real time by means of a performance collector, a state analyzer and an anomaly detector.

Systems and methods are provided for facilitating management of interactions and training for AI (artificial intelligence) agents. Systems generate and display interfaces for training AI agents and for receiving user instructions. The systems parse user instructions to identify tasks to be performed by the AI agents. The systems cause the tasks to be split into subtasks to be performed by the AI agent. The systems also display a dialog frame that presents the user instructions along with AI agent responses that identify the subtasks. The systems also display a graph that visually identifies a processing flow of the subtasks and that dynamically updates the processing flow to reflect a status of progress for the AI agent performing the subtasks.

The invention provides a DFT test task management method and device, electronic equipment and a storage medium, and belongs to the technical field of chip design verifier.The DFT test task management method comprises the steps that a data model is constructed on the basis of a design module list and a test step list, the data model is used for indicating testability design DFT test steps of all design modules, and the test steps of all the design modules are stored in the test step list; the data model comprises a plurality of DFT test tasks, attributes of each DFT test task comprise a selection state, and the selection state comprises a selected state and a non-selected state; based on the interactive input, determining at least one DFT test task of which the selection state is selected as an executable DFT regression object; and according to the DFT regression object, driving a DFT test task to be executed. According to the method, the DFT test tasks are normalized through the data model, only the DFT test tasks need to be selected for making the test plan, efficient management of the DFT test tasks is achieved, and the regression test efficiency is improved.

The invention discloses a large model corpus data interaction system and method based on a trusted execution environment, a terminal and a medium. The system comprises a data provider, a data demander and a trusted data space service platform. And the data provider is used for encrypting the corpus data, and performing preprocessing, directory sorting and packaging on the corpus data in the data provider connector to obtain the data capsule. And the data demander is used for submitting a calculation task in the data demander connector and obtaining corpus data of the data capsule for calculation after authorization. And the trusted data space service platform is used for storing the encrypted corpus data, controlling access of a data user, scheduling a calculation task, managing a key and generating an audit log. Through trusted execution environment hardware isolation and full-link encryption, it is ensured that corpus data only exists in a plaintext form in the trusted execution environment in the full life cycle from access to destruction, and unauthorized access and leakage are completely eradicated.

The invention relates to the technical field of industrial vehicle intelligence, in particular to an intelligent flexible forklift system based on multi-mode sensing and self-adaptive path planning. The intelligent forklift comprises an intelligent forklift body, a vehicle-mounted integrated control system, a multi-mode sensing and navigation module, a self-adaptive decision-making and path planning module, a cooperative communication and task management module and a cloud scheduling and management platform, and the intelligent forklift body is provided with a pallet fork mechanism with a 3D camera and a force sensor; the vehicle-mounted integrated control system serves as a core to achieve multi-module data interaction and instruction output, the multi-mode sensing and navigation module generates an environment situation map through multi-source data fusion, the self-adaptive decision-making and path planning module completes path planning, obstacle avoidance and pre-verification, the cooperative communication and task management module achieves multi-vehicle cooperation and task disassembly, and the multi-mode sensing and navigation module generates an environment situation map through multi-source data fusion. And the cloud scheduling and management platform realizes global monitoring and management. According to the method, the adaptability to complex scenes and the operation safety are improved, and accurate forking and flexible path planning are realized.

The invention discloses a task disassembling method based on a large model, and aims to automatically disassemble requirements input by a user into a series of independent and accurate minimum sub-tasks so as to support high efficiency and intelligence of task execution. Different from a traditional natural language processing method, the method adopts a large model technology to intelligently analyze and optimize input demand content, so that task description is clearer, and operability is achieved. The method comprises the following steps: firstly, deeply analyzing and adjusting a demand by utilizing the understanding ability of a large model to make the demand accord with a logic structure of task execution; then required core steps and logic levels are extracted through a multi-level task decomposition algorithm, and clear sub-task chains are generated through step-by-step decomposition; by means of the adaptability and dynamic reasoning ability of the large model technology, the decomposition efficiency and accuracy of complex tasks are remarkably improved, the burden of a user in the aspects of task planning and execution is relieved, and efficient and automatic development of intelligent task management is promoted.

The invention provides a tire crane automatic control system and method based on embedded edge calculation, and relates to the technical field of port automation, the tire crane automatic control system comprises a sensing and detecting layer used for collecting motion states and operation environment information of a cart, a trolley and a lifting appliance of a tire crane in real time; the core control layer is used for processing sensor data in real time and generating a control instruction; the action execution layer comprises a PLC gateway, a main control PLC and a driving motor, the PLC gateway communicates with the core control layer and is used for receiving a control instruction, and the main control PLC drives the motor to execute corresponding actions of a cart, a trolley and a lifting appliance; and the task management layer comprises an intelligent remote control console, is in communication connection with the core control layer, and is used for issuing the operation task instruction to the core control layer and receiving the system state data from the core control layer. Unmanned operation of the tire crane can be achieved, and a complete technical base is provided for port automation.

The invention discloses an electric power field operation management system, which relates to the technical field of electric power and comprises the following process modules: S1, planning; s1-1, an operation plan and task management module; s1-2, a power industry core combined scale block; s2, preparing; s2-1, a personnel and qualification management module; s2-2, a tool and material management module; s2-3, a risk assessment and scheme management module; s3, executing; s3-1, a field execution and monitoring module; s3-2, an emergency processing module; s4, checking and accepting; s4-1, an acceptance check and filing module; s4-2, a performance and data analysis module; s4-3, a system management module; and S5, summarizing. According to the electric power field operation management system, through systematicness and integrity of emergency plan management, a process covers full life cycle management of an emergency plan from formulation, auditing, issuing to updating, and meanwhile, links such as emergency response starting, disposal, resource management, information communication and recovery summarization are included; and a complete closed loop of prevention, preparation, response and recovery is formed.

A task management system detects condition(s) are satisfied with respect to task record(s), and triggers action(s) at least in part by substituting information from the task record(s) into placeholder(s) of user-modifiable template(s) to prompt large language model(s) for generating narrative(s) about how the condition(s) were satisfied. The triggered action(s) retrieve information from identified task record(s), substitute value(s) from the record(s) into the placeholder(s) of the user-modifiable template(s), and trigger(s) call(s) to large language model(s) to generate task completion narrative(s) or other narrative(s) for the task record(s). The narrative(s) may be stored in narrative field(s) of the record(s) for use in displaying the narrative(s) on a user interface, email notification, or other message.

The embodiment of the invention relates to the field of artificial intelligence, and discloses an agent collaborative execution system based on a task dialogue link, and electronic equipment. An agent management station; the task scheduling and execution module is used for generating a corresponding dialogue node when task scheduling is triggered each time in the process of executing the periodic task by the intelligent agent, and a plurality of dialogue nodes corresponding to the periodic task form a dialogue link according to a time sequence; the agent access and collaboration interface module is used for realizing interaction between the agent collaboration execution system and the agent; the agent workbench comprises a task management and execution viewing module which is used for responding to the periodic task execution viewing request and displaying the execution process of the periodic task in the form of a dialogue link. A dialogue link is formed by orderly connecting dialogue nodes, so that the execution process of the periodic task has a uniform and displayable data organization form, and backtracking, auditing and multiplexing of the execution process are facilitated.

Techniques are described for enabling replication-aware resource management and task management in a cloud infrastructure for cross-region replication. In some embodiments, each replication job is associated with a set of replication-related information. In certain embodiments, the replication-aware resource management allocates resources, using a combination of various resource allocation schemes, to a fleet of replicators to allow the fleet to select replication jobs in a job queue, and perform resource scaling based on monitored performance metrics reported by the fleet. In some embodiments, the replication-aware task management enables replication job selection based on the set of replication-related information to optimize the performance of all cross-region replications in the region.

The invention discloses a method and device for improving printer task management efficiency and a storage medium, and relates to the technical field of printer task management.The method comprises the steps that firstly, printing task parameters and printer real-time data are obtained, and task priorities are calculated through a task priority evaluation formula; dynamically allocating hardware and software resources according to the priority, the real-time data and a rule containing a time slice allocation formula; the states of tasks and equipment are monitored in real time, and an exception handling formula and a conflict coordination formula are used for scheduling when exceptions or conflicts occur; and finally, remaining time is calculated through a printing progress formula and a time prediction algorithm and is fed back to an interactive interface, equipment comprises a data acquisition module, a priority evaluation module and the like, a data storage and model optimization module is further arranged to optimize formula parameters, and the scheme improves task management efficiency and prediction accuracy and optimizes user experience.

The invention provides an online car-hailing driver qualification dynamic verification system and method based on multi-source information fusion. Comprising a multi-source information acquisition module used for receiving related data submitted by a driver end and performing consistency verification by using a person-certificate consistency detection algorithm to generate a first verification result; the data consistency comparison module is used for carrying out cross-certificate comparison and generating a second verification result; the automatic auditing and decision-making module is used for outputting a driver qualification auditing conclusion and a conclusion identifier according to a preset city auditing rule base and the second verification result; the training task management module is used for matching and distributing a training course task for the target driver account according to the conclusion identifier, and receiving a training completion state; and the vehicle authority control module is used for opening or keeping limitation on the order receiving authority of the target driver account according to the conclusion identifier and the training completion state, and dynamically adjusting the order receiving authority. According to the invention, rapid auditing, automatic training distribution, data linkage and real-time dynamic compliance management and control can be realized.

The invention discloses a distributed simulation method and a simulation system for centralized railway dispatching. The distributed simulation method comprises the steps of constructing a system overall architecture, constructing a simulation node management mechanism, constructing a simulation clock management mechanism, constructing a simulation task management mechanism and outputting a simulation result. According to the invention, the actual requirements of the centralized dispatching system in the aspects of simulation, training, experimental verification and the like are met, and the calculation experiment function in various emergency scenes is realized; a clock management method combining a physical clock and a logic clock realizes alignment and synchronization of node clocks at all levels under distributed speed multiplication simulation; the synchronous control of the task of each level of node under the distributed multi-speed simulation is realized.

The invention relates to a dynamic extensible heterogeneous collaborative intelligent computing platform and method for edge-end equipment, and relates to the technical field of edge intelligent computing and computer hardware, and the platform comprises a hardware infrastructure layer and a master control module for realizing signal transmission and resource sharing; the basic software layer is used for managing hardware resources and software services; the application support layer is used for running computing resources and realizing preliminary compatibility; the task management and resource scheduling layer is responsible for task arrangement and management and task scheduling decision; the application layer is used for providing various application services; the data transmission layer is responsible for transmitting data among different platforms; the computing resource interface layer provides an interface interacting with heterogeneous computing resources; and the computing resource platform is composed of different heterogeneous computing platforms and provides computing resources and computing power. The method has the capabilities of intelligent information and signal processing, diversification of application scenes, efficient parallel operation, rapid iterative development, universal flexible deployment and the like.

The invention discloses a regulation-work package bidirectional association and dynamic mapping method and system, and relates to the technical field of enterprise compliance management and task management informatization. The method comprises the following steps: constructing a standardized law and regulation library and a work package attribute library, disassembling a law and regulation file into compliance requirement points, and determining multi-dimensional attributes of a work package; forward mapping and reverse tracing binding of the compliance requirement point and the work package are realized through a mapping matching model; performing integrity, consistency and rationality verification on the mapping relation; monitoring the regulation change and automatically updating the mapping relation; and visually displaying the mapping relationship and monitoring compliance execution. The system correspondingly comprises a regulation management module, a work package management module, a bidirectional mapping module and the like. According to the method, closed-loop management and control of law and regulation requirements, task execution and compliance evidence are realized, the problems of unidirectional and static mapping and rough granularity in the prior art are solved, the compliance management and control accuracy and the dynamic adaptation capability are improved, and the compliance risk of an enterprise is reduced.

The invention relates to the technical field of heat supply network metering supervision, and discloses a heat supply network metering data supervision system based on edge calculation. The system comprises an edge data acquisition module, a metering task management module, an edge resource scheduling module and a heat supply network supervision execution module. The edge data acquisition module acquires original data from a heat supply network metering sensor in real time, and sends the original data to the metering task management module after verification and format conversion; the latter receives the data, generates and stores a metering task record according to the type and the supervision rule, and updates the state to be to-be-processed; the edge resource scheduling module queries a to-be-processed task, monitors the CPU utilization rate, the memory occupancy rate and the network delay of an edge node, determines an execution sequence in combination with the number of tasks and generates a resource allocation scheme; and the heat supply network supervision execution module activates a corresponding node, obtains a task record, executes data analysis and supervision logic processing, and stores a result. The system optimizes data processing and resource configuration by means of edge computing, and adapts to heat supply network metering data supervision requirements.

The invention discloses a multi-agent-based cross-station intelligent inspection and operation and maintenance method and system, and the system comprises an inspection expert agent, a tool use agent, a code generation agent, an overhaul expert agent and a memory module. Calling a tool using agent to obtain corresponding power station information generation suggestions, and issuing corresponding tasks after user confirmation; a code generation agent receives the task, a tool use agent is called to obtain a corresponding power station model version and hardware equipment information generation script, and script parameters are dynamically adjusted; and the maintenance expert agent obtains the script operation detection model, calls the tool use agent to obtain corresponding power station monitoring information, detects the monitoring information by using the detection model, stores the detection result to the short-term memory module, and gives a maintenance suggestion and adjusts a detection strategy by combining the detection result with the maintenance knowledge information in the long-term memory module. According to the invention, efficient, intelligent and sustainable automatic task management and execution are realized.

The invention relates to an agricultural inspection robot navigation decision planning system and a planning method thereof, and belongs to the technical field of agricultural robots, and the agricultural inspection robot navigation decision planning system comprises a multi-sensor fusion sensing module, a navigation decision planning module, a dynamic obstacle processing module, a transverse-longitudinal combined controller and a task management platform. The multi-sensor fusion sensing module comprises a laser radar, a visual sensor, a Beidou / GPS positioning module and an IMU and is used for collecting environment images, point cloud data and robot poses and recognizing crop row navigation lines through an improved YOLOX-Tiny model. According to the method, high-precision navigation can be achieved, high-precision tracking with the transverse error being smaller than or equal to 0.04 m and the longitudinal error being smaller than or equal to 0.06 m is achieved through transverse-longitudinal combined control and multi-sensor fusion positioning, the self-adaptive capacity is high, the reinforcement learning and path decomposition technology and a dynamic risk evaluation mechanism are combined, and the reliability of the system is improved. The robot can effectively deal with sudden obstacles and complex terrains in a farmland environment.

A method for automated document processing and task assignment including receiving an input document from a document source, performing a content analysis on the input document, extracting metadata from the input document, identifying an identified task type to be performed, generating standardized metadata by converting the metadata into a standardized JSON format, storing the standardized metadata in a database, determining a user assignment for the identified task type, the including an assigned user, generating an action item including the identified task type, the user assignment, and the standardized metadata, and adding the action item to a task management system for processing by the assigned user.

A task management system maintains tasks for performance by associated performing users. Each task has a set of attributes, and a performing user interacts with a task to modify a value of an attribute when the performing user works on a task. To track performance of tasks by a performing user, the task management system generates a standup report identifying interactions with tasks by the performing user during a specific time interval. The task management system identifies a set of tasks with which the performing user performed at least one interaction during the specific time interval and ranks the set of tasks based on task-specific relevance scores. A relevance score for a task is based on attributes of the task. A prompt including interactions with tasks ranked by relevance scores is provided to a generative model, which generated the standup report.

The invention discloses an Agent cooperative type long text generation system and method for a post-evaluation report, and the system comprises a specialized agent pool which is composed of at least one group of large language models with a specified tool set and an independent memory module, and is internally provided with a plurality of groups of agents of different types; the composer is used for uniformly composing and scheduling the whole report through various agents to generate a workflow; the asynchronous persistent task queue is used for driving and managing the workflow so as to realize decoupling of all system components, parallel processing of tasks and persistent operation of system states; and the mixed knowledge base is integrated with at least one group of vector databases for storing and retrieving unstructured data and at least one group of graph databases for modeling and querying complex relationships among entities. The technical problems that in the prior art, when a single AI model generates a long text report, reliability is low, logic errors are prone to occurring, and a traditional multi-agent cooperation system is poor in fault-tolerant capability and rigid in task management can be solved.

The invention discloses an MRI (Magnetic Resonance Imaging) sequence generation system and method, and the system comprises a basic sequence generator module which is used for defining an abstract base class and packaging general logic in a sequence generation process; the independent development tool chain module is used for providing a development environment independent of a system framework and compiling a sequence generator source code into a binary module; the sequence registering and loading module is used for automatically discovering and loading the binary module and registering a sequence generator class inheriting the self-abstract base class through a reflection mechanism; the RESTful API interface module is used for receiving an external request and calling a corresponding sequence generator object according to a sequence type; the asynchronous task management module is used for managing life cycles and state tracking of asynchronous tasks; and the parameter configuration management module is used for centrally managing sequence parameter configuration. According to the system and the method, the development threshold is reduced, and the expansibility, the maintainability and the concurrent processing capability of the system are improved.

An innovative system for integrating generative artificial intelligence (AI) capabilities within Software as a Service (SaaS) platforms. By leveraging advanced AI techniques, seamless data synchronization, intelligent task management, and predictive workflow optimization across multiple SaaS platforms are described. Key components include an AI-driven data synchronization system, an intelligent cross-platform task manager, and an adaptive user interface.

The invention discloses a data analysis system and method based on agent collaboration. The system comprises a front end, a context maintenance module, an agent scheduling module and a result synthesis module. The front end is used for receiving a natural language query request of a user; the context maintenance module is used for task management; the agent scheduling module is used for coordinating a plurality of agents to collaboratively analyze and query tasks through a preset state machine decision mechanism to obtain a processing result of each agent; the state machine decision-making mechanism comprises the following steps: determining a subsequently scheduled agent in combination with a current agent processing result and a current task state; and the result synthesis module is used for performing information fusion on the processing results of all the agents and the natural language query request, and outputting an analysis report to a front end. According to the method, the semantic understanding accuracy, the query analysis reliability, the execution efficiency and the practicability can be improved.

The invention discloses a business process engine system based on a micro-service architecture, and belongs to the technical field of business process engines. The business process engine system based on the micro-service architecture comprises a process design module, a process execution engine module, a task management module, a service communication module and an exception handling module. The method solves the problems that in the prior art, abnormities cannot be processed in time, and flow lag or management confusion is easily caused, the micro-service architecture and the business flow engine system are combined, a huge business flow can be split into independent micro-services according to functions, the iteration period is greatly shortened, the fast changing business requirements are met, and the method is suitable for large-scale popularization and application. The method is advantaged in that resource waste is avoided, cascade paralysis is avoided through a fusing mechanism, continuous operation of a core process is guaranteed, health state indexes of micro-services are continuously acquired, real-time alarm is triggered during abnormity, operation and maintenance personnel are helped to rapidly intervene, and operation efficiency of a business process engine is improved.

Methods for assisting one or more users in organizing content-items, such as location information (e.g., URLs) for online information resources (e.g., webpages) and clips taken from information resources, accessed via content-access software, such as one or more web browsers, using a content item-bundle primitive that allows users to create, build, manipulate, and / or populate their own content-item bundles according to their information investigation and collection desires / needs. In some embodiments, the methods include automatically bundling content items into suggested content-item bundles based on learned relationships among various content items. In some embodiments, the methods can be implemented to provide bundle-based task managers that allow users to not only organize their content items but also define tasks and / or projects rooted in the content-item-bundle primitive. Further embodiments are disclosed, as is software for executing disclosed methods.