822 results about "Multi agent technology" patented technology

An agent oriented computing environment is disclosed comprising an "agent shell" means which can be used by developers for constructing agent computing entities according to their own functionality requirements; an agent enabling layer, providing basic communication, brokering, and negotiation facilities between agent computing entities; and an underlying transport mechanism based on a prior art CORBA platform. Agents communicate with each other using an agent communication language enabling them to interact to domain specific problems. Agents can pass information to each other in ACL messages describing their own vocabularies concerning logic (ontologies). Various services for locating and connecting agents are provided in the agent oriented environment, such as a broker service for locating and finding agents. A collection of agents may communicate with each other where the agents remain static, maintaining their physical locations on their corresponding host physical resource devices, or alternatively agents may be transported across a plurality of physical resources, through the CORBA platform. The environment supports encapsulation of legacy objects, databases, standard and proprietary protocols and interfaces.

The invention relates to an MAS-based (multi-agent system) multi-microgrid energy management system simulation method. The method is characterized in that a multi-microgrid energy management system is divided into a local management layer, a microgrid management layer and a microgrid coordinated management layer in different levels; various energy management functions of the different layers are used to establish a multi-microgrid energy management system model by different types of agents, and agent communication protocol is designed for coordination and convention of the agents. The agents in different control layers of the local management layer, the microgrid management layer and the coordinated management layer are integrated by a client-server architecture, and accordingly an MAT-based (multi-agent technology-based) multi-microgrid energy management system simulation platform is formed. The method is provided to verify different microgrid control strategies and scheduling plans.

A one number, multi-application, intelligent call processing system provides service benefits to a caller, a servicing location and / or a vanity number advertiser during a call, parallel to the call and / or post call in an integrated common architecture. The system utilizes VRU technology in conjunction with the national telecommunications network connected via Computer Telephone Integration (CTI) to a virtual telephone number database containing a nationwide master list of telephone numbers with attribute data items associated by Spatial Key linkage to each telephone number. The process of the invention is initiated by a caller dialing a selected telephone number to request information and / or services. Based on the number dialed, a caller or network provided ten-digit telephone number and VRU prompted for and received caller input, the system retrieves the application requested data from the virtual telephone number database and provides it to the network.

The invention relates to a multi-agent reinforcement learning scheduling method, a multi-agent reinforcement learning scheduling system and electronic equipment. The method comprises the following steps: step a, collecting server parameters of a network data center and virtual machine load information running on each server; b, establishing a virtual simulation environment by using the parametersof the server and the load information of the virtual machine, and establishing a deep reinforcement learning model of multiple agents; c, performing offline training and learning by utilizing the deep reinforcement learning model of the multiple agents and a simulation environment, and training an agent model for each server; and d, deploying the agent model to a real service node, and schedulingaccording to the load condition of each service node. The service running on the server is virtualized through the virtualization technology, load balancing is carried out in a virtual machine scheduling mode, resource distribution is more macroscopic, and a strategy that multiple agents generate cooperation in a complex dynamic environment can be achieved.

The present invention relates to multi-application, secure operating systems for small, secure devices, such as smart card microcontrollers. In particular, the present invention relates to mechanisms for secure runtime upload of applications onto small devices, authorisation mechanisms and the ability for authorised execution of multiple applications on the devices, where an application may be potentially larger than the microcontroller memory size. The mechanism simplifies life-cycle smart card management aspects related to post-issuance application (“applet”) upload and upgrade. Mechanisms to prepare applications (i.e. compiler techniques) using a common set of project files in one compiler toolset, for execution in a dual host & chip processor environment are described. These help automising the programming of the communication interfaces between the host and chip applications. An important motivation for the present invention is to provide a secure co-processor environment for general computer applications in order to counter software piracy, and to allow new models for secure electronic software distribution and software licensing.

Tools and techniques for collecting data from target systems without the need for installation of expensive and high-maintenance software agents on the target systems. In some cases, these tools can be used to collect performance data from collection targets while still allowing the operator(s) of the collection targets to govern the access of the tools, alleviating security concerns. Merely by way of example, certain tools employ data collection scripts, which may be analyzed by the collection target against security policies of that collection target, to ensure that the scripts will not take any actions that might violate such security policies. Other tools may be used to collect data in real time by transmitting a script for immediate execution by the host system, which could then return the data produced by the script immediately upon completion (and / or as part of execution of the script).

The invention relates to a micro-grid coordination control system based on multi-agent technology, pertaining to the information technology field, wherein an element agent module independently controls the operation of bottom elements in the micro-grid, realizing direct control on a distributive power source, power generation, power-reserving elements and some loads; a micro-grid agent module operates in accordance with the internal dispatching of the micro-gird and manages the agents; task division and shared resource allocation among agents are solved by communication and coordination between the micro-grid agent module and an upper grid agent module, and the upper grid agent module takes charge of the coordination and dispatching in the electric market and among agents and makes the important decisions by integrating information of the micro-grid agents. A certain amount of data communication among the agent modules are kept for better ensuring rationality for decisions made by each agent. The structure and the communication method fit the complex and flexible characteristics of micro-grid distribution. The coordination control system can promote the safe and steady operation of the micro-grid as well as the generating efficiency.

Techniques for managing a system of heterogeneous applications are provided. A plurality of applications is classified into a plurality of application types. One or more of the plurality of applications in each of the plurality of application types are classified into one or more collections. A utility function of possible resource allocations is computed for each of the one or more collections. An application placement is computed that optimizes a global utility of the plurality of applications in accordance with the one or more utility functions. Placement and resource allocation of the plurality of applications are modified in the system in accordance with the application placement.

Techniques for improving the performance of a quantum processor are described. Some techniques employ reducing intrinsic / control errors by using quantum processor-wide problems specifically crafted to reveal errors so that corrections may be applied. Corrections may be applied to physical qubits, logical qubits, and couplers so that problems may be solved using quantum processors with greater accuracy.

Disclosed systems and methods mitigate interference in heterogeneous networks. Embodiments include adaptive or selective inter-cell interference coordination, adaptive multi-user zero forcing, adaptive power, and / or combinations of the foregoing. Techniques may be used to favor one group of users (e.g., femto users or macro users) over another. Certain embodiments focus quality of service (QoS) improvements on a first group of users, while using constraint processes to provide a threshold QoS for a second group of users.

The invention discloses a multi-agent-based platform scheduling intelligent sorting model structure. Steel material logistics distribution belongs to heavy-duty transportation in transportation and needs special handling equipment and large-scale transportation vehicles. In a distribution and loading process, the loading efficiency and sequence (platform scheduling) of vehicles are directly related to distribution aging. Platform scheduling is a multi-constraint combination optimization complex system. Reasonable ordering and optimization are essential. According to the invention, a multi-agent technology is used to research real-time vehicle scheduling decisions; a combination optimization complex system using a platform-based scheduling ordering system and multi-agent algorithm design as multiple constraints is constructed; a multi-agent technology provides a new solution for the research of real-time vehicle scheduling decisions to improve the efficiency of freight operations; the optimal solution is acquired; an auxiliary vehicle identification technology is used to carry out whole-process monitoring on distribution vehicles; efficient vehicle scheduling and precise handling are realized; and precise steel material distribution is realized.

The invention discloses a cloud architecture system of two-dimension code application, relates to the relative mobile internet technology, the two-dimension code technology, the geographic positioning technology and the telecommunication technology, and provides a comprehensive cloud architecture bottom platform support and a series of solutions to two-dimension universal application. The comprehensive cloud architecture bottom platform can effectively overcome difficulties existed in current two-dimension application, and particularly solve the problems that two-dimension information data integration which cannot be realized by the prior art but is needed to be realized is effectively built up between a buyer and a user to realize combination of simple and convenient businesses. Therefore, the two-dimension code application technology can be widely applied and popularized on-line and off-line among a buyer, a user and a third-party platform.

The invention discloses a multi-agent and heterogeneous communication technology based micro-grid intelligent measuring and controlling terminal, a multi-agent system and a measuring and controlling method of the multi-agent system. An element Agent, a micro-grid Agent and an upper-stage power grid Agent form a micro-grid multi-agent system. The intelligent measuring and controlling terminal comprises a master control module, a data acquisition module, a protection control output module and a heterogeneous communication module. The data acquisition module acquires real-time data information of base layer elements in the micro grid, the master control module stores and processes the real-time data information and sends the real-time data information to an upper micro-grid Agent through the heterogeneous communication module. Meanwhile, the master control module receives control instructions of the micro-grid Agent through the heterogeneous communication module and transmits the control instructions to the base layer elements in the micro grid through the protection control output module to control the work states of the elements. The intelligent measuring and controlling terminal and method have the advantages of being capable of achieving mutual communication of micro-grid complex heterogeneous communication networks, wireless, small in size, low in power consumption, low in cost and capable of improving the micro-grid safe and stable operation and power generation efficiency greatly.

The invention discloses an ant colony optimization processing method of large-scale multi-target intelligent moving route selection; after data of NTSP target logistics delivery addresses, distances between every two addresses, and M price of cost for passing through each route are obtained, a route planning unit is solved by ant colony optimization technology so as to obtain a specific walking route for intelligent mobile-agent delivery, and the route is outputted to an executive mechanism for realization. When the method is used to solve the problem of large-scale multi-target intelligent moving route selection, the invention has good optimization performance, and has the advantages of parallelism, self-organization, strong robustness, and the like, and the obtained solutions are large in quantity, high in quality, and have strong approximation capability to the real Pareto solution set; the obtained solution set has uniform distribution; the calculation speed is high. The inventioncan be used in intelligent processing units of route planning systems in fields of logistics distribution, intelligent traffic, internet, robots, etc.

The invention provides an event trigger based multi-agent consistency control method, which enables information communication to be conducted among multiple agents only when an event trigger occurs, thereby reducing the calculation processing load of an agent processor and the communication frequency among the multiple agents. Meanwhile, digital channel communication is adopted among the agents, and a dynamic coding and decoding quantization mechanism, which reduces network bandwidth occupation, is set for a communication instruction, thereby enabling the data communication amount in each time to be also reduced, and greatly alleviating the network transmission load. In addition, a consistency control scheduling scheme which combines a self-operation control strategy and an event trigger based self-regulation control strategy is further adopted, thereby being capable of realizing effective multi-agent consistency control, and thus effectively solving a problem in the prior art that a multi-agent consistency control mode relying on real-time continuous information exchange is difficult to be implemented or disordered in multi-agent cooperative control in realistic network application conditions.

The embodiment of the invention provides a reinforcement learning training optimization method and device for multi-agent confrontation. The method comprises the following steps of a rule coupling algorithm training process including the steps of acquiring an initial first state result set of a red party multi-agent for each training step, if the initial first state result set of the red party multi-agent meets a preset action rule, obtaining a decision-making behavior result set according to the preset action rule, and otherwise, acquiring the decision-making behavior result set according toa preset reinforcement training learning algorithm; and performing reinforcement learning training on the red-party multi-agent by utilizing a training sample formed by the decision-making behavior result set and other preset parameters. The embodiment of the invention provides the reinforcement learning training optimization method and device for multi-agent confrontation. In the whole training process, the preset action rule can guide the multiple agents to act, invalid actions are avoided, the problems that in the training process in the prior art, invalid exploration is much, and the training speed is low are solved, and the training efficiency is remarkably improved.

An object of the invention is to provides a particle swarm optimization method based on a multi-strategy synergistic function. The technical scheme of the method comprises a first step of initializing a particle swarm, wherein NP particles are initialized, a second step of calculating fitness values of the NP particles, a third step of determining particle speeds and position change modes, a fourth step of executing Cauchy variation on positions of the particles, and a fifth step of determining a particle execution stop condition. The method is suitable for optimization solving of a function, takes the full advantage of elite reverse learning, and improves a function optimization speed and function optimization precision; and the particles are prevented from falling into a local optimal value by utilizing gauss variation, and variation is performed on the positions of the particles by utilizing the provided Cauchy variation a Cauchy distribution proportion parameter of which decreases linearly and progressively, so more excellent particles are generated to guide other particles to move toward a better solution direction, the function optimization precision is improved, and function optimization stability are also improved.

The invention discloses a multi-robot route planning method applied to a dangerous chemical environment, and belongs to the technical field of robot route planning. The method is applied to intelligent robots, can realize full map inspection of multi-robot under a complex and dangerous chemical environment with high dynamic performance, and can realize real-time formation reaction to special events. The core algorithm of the method is a deep reinforcement learning algorithm combined with a deep deterministic policy gradient and a curiosity driven algorithm. According to the core algorithm, thecomplex and tedious step of artificially designing environment rewarding in the same kind of algorithm are avoided, while the unknown complex environment is explored and adapted through the intrinsicrewarding and the sparse environment rewarding in the intelligent body itself; and meanwhile, a multi-Agent collaboration learning algorithm is adopted among the multi-robot to obtain the optimal cooperation strategy.

The invention discloses a hybrid electric vehicle energy management system and method based on a multi-agent technology. The energy management system comprises a signal collecting agent, a prediction agent, a storage battery agent, an energy management agent and an execution agent. The signal collecting agent collects vehicle condition information and environment information of a vehicle through a data collecting unit and transmits the information to the prediction agent, the prediction agent predicts the running conditions of the vehicle in the next small section of road and transmits the predication information to the energy management agent, the energy management agent calculates the vehicle energy optimal distribution according to the information transmitted by the prediction agent and the information transmitted by the storage battery agent and transmits distribution commands to the execution agent, and finally the execution agent executes a distribution scheme of energy between an engine and a motor. By means of the system, the running conditions of the vehicle in the next small section of road can be predicted in advance, energy management optimal control is conducted, the purpose of optimization is achieved, and the fact that a whole running condition is required in order to conduct overall optimization is avoided.

The invention relates to the technical field of networked control systems, in particular to a method for determining a consistent event trigger controller aiming at the condition that a multi-agent system with a leader has denial of service attack (DoS) by utilizing a modal dependent average residence time method, comprises the following steps of: step one, establishing a leader-follower multi-agent system model and a design event triggering condition; step two, establishing a DoS attack model and a switching system model; step 3, designing an event trigger controller and corresponding switching conditions. The average residence time method adopting modal dependence solves the design problem of the consistent event trigger controller in a leader-follower multi-agent system with DoS networkattack.

The invention discloses an application program dual-opening method and device, and belongs to the field of electronic devices. The application program dual-opening method includes: installing a designated original application program in a system through a primary account, allocating a first resource catalog to the original application program, and setting the operation authorization for the first resource catalog through an identification of the original application program and the primary account; and installing a dual-opening application program identical to the original application program in the system through a secondary account, allocating a second resource catalog to the dual-opening application program, and setting the operation authorization for the second resource catalog through an identification of the dual-opening application program and the secondary account, wherein the original application program and the dual-opening application program are permitted to open at the same time, and the identification of the original application program and the identification of the dual-opening application program are identical. The application program dual-opening method and device can solve the problem that user data has potential risks in the relevant technologies, and can improve the security of the user data.

The invention relates to a VM migration strategy under a mobile edge computing environment in a 5G network, and belongs to the technical field of mobile communication. The service migration strategy in the existing research neglects task unloading cost in QoS requirements of users, and task division in the existing research is mostly a coarse-grained model or a fine-grained chain model and is notsuitable for complex association scenes among subtasks. Problem for migration decisions, According to the method, fine-grained directed acyclic graph division is performed on tasks, a task time delaymodel and an unloading cost model are established, the VM migration decision problem of minimizing task unloading cost under the time delay constraint condition is constructed, and finally, migrationdecision is performed on the basis of a genetic algorithm to obtain a virtual machine migration decision result of each subtask. The method and the device have important significance for ensuring theservice continuity of user task unloading and meeting QoS requirements.

The invention discloses an unmanned cluster task collaboration method based on multi-agent reinforcement learning, and belongs to the technical field of unmanned cluster task planning. According to the method, the method comprises the steps of: establishing a reinforcement learning simulation environment for task planning of the multi-unmanned system based on Unity; using Gym to build the acquired information of the simulation environment into a reinforcement learning environment conforming to the specification; modeling an unmanned aerial vehicle cluster confrontation environment; using a Tensorflow deep learning library for building a multi-agent reinforcement learning environment; solving a multi-agent reinforcement learning problem by using a collaborative depth deterministic strategy gradient method; and outputting an unmanned cluster task planning result. According to the method, the prior art is greatly improved, and a better multi-unmanned-system cooperative task planning result can be obtained.

The invention discloses a networked multi-agent system distributed optimization control method based on reinforcement learning, which belongs to the technical field of system control methods. A Bellman equation with an integrator is provided for integral reinforcement learning (IRL). According to a non-strategy (Off-poly) method, different control strategy action control systems are applied, dataexploration is added, an optimal control strategy is obtained through iterative learning, a graph game is fused with Off-poly and IRL, and the consistency of networked multi-agents is ensured under the condition that a system model is completely unknown. The system comprises the following specific steps: (1) solving an optimization control problem based on IRL and Off-poly; (2) iteratively designing a distributed approximate optimal control strategy based on an approximate strategy; and (3) adopting simulation software and a multi-manipulator control system physical experiment platform, and correspondingly adjusting a theoretical method and a control technology according to simulation and physical experiment results.

The invention discloses an agent-based construction method and device of an intuitionistic fuzzy theory medical diagnosis model. With the adoption of a sensor technique and an artificial intelligence technology, remote and automatic acquisition and transmission of patient symptom are achieved; diagnosis analysis is carried out on the patient symptom by an intelligent medical diagnosis model built based on an intuitionistic fuzzy theory; the patient symptom is continuously updated and completed by a systematic knowledge module, namely a symptom-disease knowledge base and a disease-medicine knowledge base, and the diagnosis effect of the system is improved and enhanced; and on the condition that the existing medical staff, resources and technology are limited and the ageing population of China is faster, agent-based intelligent medical diagnosis system (AIMD) design is changed to ATM in a substantialization way and is installed in an aged community, convenient and high-efficiency medical services are provided for a patient through self-service terminal services, and the medical stress is effectively relieved. By the medical service mode, the medical clinic time is saved, and the medical cost is also reduced.

The invention provides and establishes a multi-agent frame structure based tour multimedia information personalized service system. The system adopts the Agent technology, finds and mines interests of users through constant independent study, and realizes automatic user interest modeling by adopting a vector included angle based K-nearest neighbor algorithm. As for each phase of a system working process, modules with relatively independent functions are divided, and each module is packaged into an Agent agency to form a multi-agent framework; and under the framework, the agencies are separated and cooperated so as to realize the characteristics of intelligence, personalization and the like of the multimedia information service. The system mainly comprises five functional modules, namely a user interface Agent, a filter sequencing Agent, an interest study Agent, a monitoring Agent and an information searching Agent. The method proposed by the invention has higher theoretical significance and application value for establishing high-quality intelligent tour information service.

The invention belongs to the technical field of artificial intelligence. The invention discloses a multi-agent cooperation information processing method and system, a storage medium and an intelligentterminal. Each agent reserves own information trace in the environment when taking the next behavior in the environment, searches surrounding information trace when other agents reach the state in the environment, and adds the information trace into the neural network for training; the grouping model finds a better cooperation strategy among the multiple agents, and the grouping model predicts the optimal grouping of the multiple agents at the next moment by using the grouping relationship among the multiple agents; when one round of training through the G model is finished each time, the loss function formula of each agent is regarded as fitness, the loss value mean value of each round of intelligent agent trajectory is counted, and the loss values of all agent trajectories of each roundare summarized. According to the method, the team learning efficiency of the multiple agents is improved, and the multiple agents can better complete tasks through team cooperation.

The invention relates to a multi-agent anomaly detection method based on the Internet of things, which is an anomaly detection method for a wireless multimedia sensor network. In the method, the multi-agent technology is introduced mainly to solve the problem of the abnormal situation in the operating process of the wireless multimedia sensor network. The scheme of the multi-agent anomaly detection system is characterized in that: coordinating through a local agent, and monitoring a local sensor network autonomously, independently and promptly; when the terminal finds that the audio / video and other data are abnormal or the network needs regular maintenance, detecting whether the network is abnormal through issuing global agency; and if the abnormal situation occurs to the network, repairing the network dynamically and autonomously to ensure the correct operation of the network. The method of the invention can promptly detect whether the abnormal situation occurs to the network, and repair the network within a limited period to restore the normal operation of the network. Moreover, the invention can reduce the network congestion rate, balance the energy consumption of the network, efficiently utilize resources of the total network, improve the fault tolerance of the network and ultimately prolong the life cycle of the entire network.

The invention discloses a hybrid virtualization cloud computing resource optimal control method and a system catering to an X86 / POWER hybrid virtualization cloud computing resource management platform in the technical field of cloud computing information processing. Through receiving applications of the cloud resource management platform, agent requests comprising virtual machine building, virtual machine destroying, virtual machine starting, virtual machine stopping, virtual machine backing-up and virtual machine state checking are sent; after the agent requests are analyzed, corresponding processing instructions are sent to virtual machine servers with different architectures; and finally, corresponding responses of the processing instructions are received and are returned to the applications of the cloud resource management platform to realize the optical resource control. The method and the system use the operation of the applications of the cloud resource management platform without considering the characteristic of different architectures of hybrid virtualization servers, so that the management control mode for the virtual machine resources is simplified.

The invention discloses a task planning method for autonomous cooperation of an unmanned aerial vehicle cluster. The method comprises the steps of obtaining and distributing a task request; selectinga single Agent task; broadcasting a selection result and a target satisfaction value to the outside; acquiring broadcast information of other Agents; carrying out multi-Agent conflict elimination; broadcasting task planning results. According to the method, the electromagnetic space environment of actual flight of the unmanned aerial vehicle is fully considered, distribution autonomous planning isprovided, compared with the prior art, the method has higher reliability and stronger robustness, no central computing node exists, the system does not only depend on any node, and when the node breaks down, the overall function of the system cannot be affected; the method has the advantages of short communication time delay and low calculation complexity, and each Agent can realize autonomous planning and control by only needing part of information and own states of other Agents, so that the calculation complexity is greatly reduced, and quick response to battlefield environment change can be realized.