16 results about "Cooperative behavior" patented technology

The application discloses a multi-resource task planning method and system based on reinforcement learning and performance evaluation, and the target task is subjected to resource calculation and cooperative strategy calculation based on a target behavior threat library, a task resource library and a cooperative strategy library which have been constructed to obtain a cooperative planning strategy; different means task resource data are accessed through a network, and the data are collected and analyzed through middleware to form a multi-means task resource library; and the application forms a heterogeneous task resource cooperative behavior strategy according to existing task resource occupation conditions and target behavior threat analysis calculation, and supports multiple task resources to cooperatively complete the same target task.

The invention relates to the technical field of artificial intelligence, and discloses a multi-unmanned equipment cooperative behavior decision method and system, and the method comprises the steps: carrying out the normalization packaging of a heterogeneous perception stream, and obtaining an original data array; mapping the spatial-temporal characteristics of the original data array to preset environment priori knowledge, and performing situation structured reconstruction on the spatial-temporal characteristics and a characteristic dimension and a spatial topological relation of the environment priori knowledge to obtain a situation map; performing joint strategy optimization solution on the multi-agent behavior intention of the situation map to obtain a collaborative behavior intention track; performing instruction granularity coding on the collaborative behavior intention trajectory to obtain an atomic operation instruction sequence; distributing the atomic operation instruction sequence to multiple unmanned devices, and performing global execution barrier establishment on the multiple unmanned devices to obtain a synchronous execution event; performing gradient updating on strategy generation parameters of the multi-agent decision network to obtain a collaborative decision optimization network; according to the invention, the efficiency of cooperative behavior decision-making of multiple unmanned devices can be improved.

The invention discloses a mouse cooperation behavior experimental device, and relates to the technical field of biomedical engineering and animal behavioristics experimental equipment. The device comprises a box body which is divided into two adjacent cavities by a porous partition plate, wherein a nose touch detection module and a reward module are respectively arranged on two opposite side walls in each cavity. The master control unit is based on the microcontroller, is connected with the infrared sensor and the execution mechanism, and executes cooperation judgment logic: only when it is detected that the nose touch detection modules of the two cavities are triggered at the same time in a preset time window, the award module is controlled to release awards, and a synchronous marking signal is output. By utilizing a sensory communication environment and an automatic control technology, the problems that an existing device is low in synchronous detection precision and limited in interaction are solved, and efficient induction, training and multi-modal data synchronization of mouse cooperation behaviors are achieved.

This invention discloses a hardware root-anchored AI cluster collaborative behavior global constraint system, belonging to the field of distributed intelligent cluster security management technology. This invention adopts a core architecture of cross-device unified hardware root authentication and distributed hardware cross-verification, supporting multiple compatible implementation forms such as local certificate chains, node permission hierarchies, and offline consensus, and is fully compatible with existing single-machine isolation protection systems. By unifying the hardware trust root, implementing fully offline hardware verification, and hardware-level permission control, this invention addresses the industry gaps where fragmented single-machine protection cannot manage cluster collusion and offline autonomous control failures; it adapts to various cluster security upgrade technology evolution scenarios and is suitable for long-term compliant management of all types of unmanned formation and distributed AI clusters.

This invention relates to the technical field of military intelligence and computer vision, and discloses a method and related equipment for recognizing collaborative tactics in beyond-line-of-sight high-dynamic dual-aircraft formations. The method includes: constructing a spatiotemporal graph that fuses intra-frame spatial connectivity and inter-frame temporal correlation based on the three-dimensional spatial coordinates of each enemy aircraft and the dynamic distance between friendly and enemy aircraft in continuous frame data; inputting feature vectors into a two-layer cascaded spatiotemporal feature extraction network, where each layer sequentially performs adaptive spatial graph convolution and parallel temporal feature fusion. The adaptive spatial graph convolution extracts collaborative features of the dynamic space of the dual-aircraft nodes within the frame, and the parallel temporal feature fusion extracts local short-term maneuver detail features and global long-term features in parallel based on the collaborative features, and then fuses them; outputting the recognition result of the collaborative tactical type performed by the dual-aircraft formation. Through the above method, this invention can comprehensively improve the accuracy of tactical recognition.

The invention discloses a multi-source heterogeneous public opinion risk assessment method and device based on a dynamic weight. The method comprises the steps of obtaining first data representing a historical normal association mode between information release accounts; obtaining second data of an instant collaborative behavior mode displayed by an account group participating in the specific public opinion event in a preset time window after the event occurs; comparing the first data with the second data, and analyzing the difference between the association state between the accounts in the historical normal association mode and the collaboration state between the accounts in the instant collaboration behavior mode; the method comprises the following steps: comparing a historical normal association mode of an information release account with an instant collaborative behavior mode when a specific event occurs, so as to identify an account cluster which is low in normal association degree but is abnormally high in collaborative degree in the event; and the effect of effectively discriminating the account cluster which is subjected to strategy information control after trust is obtained through long-term camouflage is achieved.

The invention discloses a service process-oriented adaptive data security and authority management method, and particularly relates to the technical field of data security and authority management.The method comprises the following steps of: firstly, modeling a target service process, acquiring nodes, a main body, an environment and data attributes, forming an access event, and constructing a dynamic trust chain network with a trust state; secondly, a collaborative behavior path is generated around the sensitive data in a sliding time window, a risk score is calculated in combination with path frequency, a topological structure and cross-organization and cross-role characteristics, and a high-risk collaborative behavior path is recognized. And then multi-granularity candidate permission intervention measures are generated for a high-risk path, risk benefits and service influences are comprehensively evaluated, and subject-level, session-level, resource-level and path-level permission adjustment strategies are automatically generated, issued and executed. And finally, the trust state and the feature weight are dynamically updated based on a strategy execution result and auditing feedback, and continuous and accurate interception of abnormal cooperative behaviors and minimization of influence on services are realized.

The application discloses a cross-regional teacher cooperative pairing recommendation method and system based on causal relationship discovery, and belongs to the technical field of education informatization and intelligent decision support. The method comprises the following steps: collecting five-dimensional ability scores and basic attribute information of teachers, and constructing a digital portrait vector; based on historical cooperative behavior logs and ability change data, a hybrid causal discovery method combining Granger causality test and convergent cross mapping is adopted to construct a causal knowledge graph between cooperative behavior and ability improvement; for a candidate pairing combination, based on the causal knowledge graph and the digital portraits of both parties, the expected ability gain is calculated in a directional manner, and a two-way empowerment index is obtained by weighted summation; the two-way empowerment indexes of all candidate combinations are sorted to generate an optimal pairing recommendation scheme. The application first introduces a causal discovery method in the field of education cooperative pairing recommendation, so that the recommendation result has causal explanatory power, the dimensional ability gain of the candidate combination can be quantitatively predicted before the implementation of pairing, and the method is suitable for small sample scenes with limited participating teachers, and provides data-driven intelligent decision support for accurate pairing of teachers in cross-regional education cooperation.

The invention relates to the technical field of ships, and provides a method and a system for identifying a forged ship trajectory, electronic equipment and a storage medium. The identification method for the ship counterfeit trajectory comprises the following steps: acquiring AIS data and a graph auto-encoder model; extracting a ship track of each ship and ship information of each ship from the AIS data; according to the ship trajectory and the ship information of each ship, constructing a cooperative behavior map among the plurality of ships; determining an abnormal value of each ship trajectory according to the cooperative behavior map and a map auto-encoder model; and determining a forged trajectory according to the abnormal value of each ship trajectory. According to the method, the cooperative behavior graph between the ships is constructed, and the graph auto-encoder model is utilized to automatically learn the cooperative rule of the normal ship group so as to identify the forged track, so that the method does not depend on manual labels any more, and the forged track can be automatically found under large-scale AIS data without labels.

The application relates to the technical field of robot control and intelligent optimization, and discloses a multi-axis robot cooperative control method based on a swarm intelligence algorithm, which collects multi-axis robot operation state data and constructs a topological structure diagram; the topological structure diagram is input into a Graphormer model to generate a cooperative behavior embedding vector; a multi-objective fitness function is constructed based on the cooperative behavior embedding vector; an RDPSO algorithm is used to optimize a cooperative trajectory; trajectory decoupling is performed to generate independent control instructions and adjust local control parameters; after monitoring execution deviation and cooperative state changes, a re-optimization process is triggered to optimize the target cooperative trajectory; and based on joint output, a future cooperative state prediction result is generated. The application realizes high-precision trajectory planning, real-time re-optimization and cooperative prediction of multi-axis robots in cooperative tasks, improves system cooperative efficiency, safety and robustness, and is suitable for cooperative manufacturing, intelligent equipment and flexible production scenes.

The application discloses a kind of based on predator mechanism's no navigation structure group confrontation method, including steps Step1.Acquire no navigation structure group information;Step2.Analysis no navigation structure group movement model;Step3.Develop predator movement model;Step4.Predator implements the destruction to group structure;Step5.Determine confrontation effect;The above-mentioned method of the application describes the communication characteristics and cooperative behavior characteristics of no navigation structure group by analyzing fish school emergence mechanism and movement model, and a corresponding predator model is designed accordingly, and the cohesion and centripetal property of no navigation structure group are destroyed by the predator, to realize the effective confrontation to the whole no navigation structure group.The predator model proposed in the application is simple, can realize the effective confrontation to no leadership structure group with point-to-surface, and has the advantages of high confrontation efficiency ratio.

This invention relates to the fields of computer simulation and smart elderly care technology, and discloses a method, terminal, and storage medium for simulating the collaborative behavior of intelligent agents in elderly care institutions. The method generates intelligent agents in a three-dimensional virtual simulation environment and assigns a multi-level identity tag system to each agent; it identifies elderly intelligent agents in a state of inability to move independently and sets them as anchor points for nursing task interactions; intelligent agents with mobility generate dynamic perception domains centered on themselves in real time and perform multi-dimensional state perception based on spatial proximity; when a target intelligent agent is detected within the perception domain of a service personnel intelligent agent and preset matching conditions are met, the corresponding collaborative mode is activated; the method calculates the joint path of the collaborative group or the individual service station, drives the intelligent agents to execute corresponding interactive animations, and, during path movement, executes dynamic avoidance logic under group conflict based on preset social behavior rule priorities. This invention realizes the simulation of the entire process from bedridden to out-of-bed transfer.

The invention discloses a photovoltaic cleaning robot scheduling method based on multi-agent cooperation, and the method comprises the following steps: carrying out the region division, and generating a consistent reachability topological matrix; data are collected and processed to generate regional cleaning value parameters, and a regional attribute set is formed; an ant population and an ant lion population are initialized, and a multi-agent initial candidate scheduling scheme set is generated; executing random walk and restricted area transfer, and generating a multi-agent candidate scheduling scheme set; performing basic fitness calculation to generate a basic fitness value; detecting an area and channel path occupancy relation, and adding conflict punishment to form a collaborative fitness value set; generating a next-generation candidate scheduling scheme set meeting the reachability topological matrix and the cooperative behavior constraint according to the updating rule; and selecting a target scheduling scheme, and distributing the target scheduling scheme to the plurality of photovoltaic cleaning robots for cooperative execution. According to the method, multi-agent collaborative scheduling is realized by adopting improved ant lion optimization, and a reachable, efficient and conflict-free scheduling scheme is generated.

The invention discloses a data cross-border risk monitoring method and device based on data flow path rich information, and the method comprises the steps: dynamically collecting data cross-border flow path information, constructing a heterogeneous multi-relation space-time hypergraph, abstracting a data related main body into a node, building a multi-type edge according to a data behavior, and carrying out the data cross-border risk monitoring. Nodes and edges carry multi-dimensional attributes, and the hypergraph is dynamically updated; rich information features are extracted from four levels of nodes, edges, paths and global graphs on the basis of the hypergraphs; and constructing a cooperative behavior relation graph based on the features, mining a cooperative behavior mode, and carrying out anomaly recognition and judgment, thereby realizing multi-subject cooperative abnormal behavior monitoring. According to the method, the rich information of the data flow path is fused, so that the multi-subject path anomaly and collaborative anomaly mode under the global view can be effectively identified, the comprehensiveness and accuracy of data cross-border risk monitoring are improved, and the data outbound security is guaranteed.

The invention relates to an entity interaction configuration method and device, equipment and a medium. The method comprises the following steps: in response to an interaction instruction for a first interaction component in a game scene, scheduling a virtual interaction entity currently associated with a player character to a target interaction position associated with the first interaction component based on the instruction; determining a corresponding cooperative behavior logic based on an interaction task type pre-associated with the first interaction component, and controlling the virtual interaction entity scheduled to the target interaction position to execute a corresponding cooperative interaction operation based on the cooperative behavior logic; and dynamically updating a visual performance state of the first interaction component in the game scene according to an execution result of the collaborative interaction operation, and synchronously updating state prompt information corresponding to the first interaction component in the game interface. According to the invention, through unified scheduling, collaborative execution and state synchronization mechanisms based on task types, flexible and extensible interaction process, real-time consistency of behavior feedback and improvement of overall user experience are realized.

The invention provides a multi-vehicle homogeneous cooperative behavior decision-making method and device. The method comprises the following steps: acquiring information and environment perception information of a plurality of vehicles in a target area; the vehicles comprise controllable vehicles and uncontrollable vehicles; determining the energy intensity distribution of a front area of any target controllable vehicle based on the information of the multiple vehicles in the target area; determining a first feasible region of any target controllable vehicle based on the environmental perception information and the energy intensity distribution of the region in front of any target controllable vehicle; determining a second feasible region of any target controllable vehicle based on the excitation value of the first feasible region of any target controllable vehicle; and according to a preset cooperation strategy, the second feasible region of the controllable vehicle with the conflict is eliminated. According to the invention, homogeneous, generalized, efficient and safe cooperative behavior decision of multiple vehicles in a complex road scene can be realized.