103 results about "Behavior control" patented technology

The embodiment of the invention provides a game role behavior control method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring a plurality of time sequence paths generated based on interaction points in a game scene, wherein the interaction points are scene components for game roles to interact; determining the strategy value and access feasibility of each interaction point on each time sequence path; based on the strategy value of the interaction point, determining the overall strategy value of each time sequence path; determining a target time sequence path and an interaction point access time sequence on the target time sequence path based on the overall strategy value of the time sequence path and the access feasibility of each interaction point; and controlling the game role to access the time sequence to execute the target behavior based on the target time sequence path and the interaction point on the path. Through overall strategy value evaluation of a time sequence path, the problem of short view or stiffness of an AI decision in the prior art is solved, so that an AI role can select an optimal path based on long-term benefits; meanwhile, through dynamic calculation of access feasibility, decision failure caused by infeasible paths is avoided, and the real-time adaptability and simulation degree of AI behaviors are improved.

The invention relates to the field of home safety, in particular to an AI intelligent home safety control system. Comprising a management center, and the management center is in communication connection with a home user behavior module, a home user control module and a safety detection control module. Acquiring historical instruction data of a user for the smart home, analyzing the historical instruction data, constructing a user instruction map, and generating user control data in combination with the user instruction map; constructing a network path link in combination with the historical instruction data and the user control data; analyzing the network path chain to generate a standard path chain template; generating a real-time home path chain through the obtained current control behavior of the user, and obtaining a home behavior control model according to the user instruction map and the network path chain; and analyzing the collected real-time instruction data in combination with the home behavior control model, generating a risk mapping index table, and performing safety control on the smart home through the risk mapping index table. According to the invention, the security of the smart home can be improved.

The invention discloses a digital twinning-oriented animation linkage method and device, equipment and a storage medium. The method comprises the steps that based on classes in a domain ontology model and attributes of the classes, operation data of the Internet of Things system are converted into first semantic data, and the domain ontology model comprises an environment class, an equipment class and a behavior class; performing event identification on the first semantic data to obtain a first event; reasoning the first event based on a preset reasoning rule set to obtain a first reasoning result, the first reasoning result comprising a first response behavior for the first event; and controlling a digital twinborn body corresponding to the Internet of Things system to execute an animation matched with the first response behavior. Therefore, a closed-loop control chain of data driving, semantic recognition, event reasoning and animation linkage is formed, high reliability is achieved, complex dynamic linkage is supported, and therefore intelligent, automatic and visual expression of the system is effectively improved.

The invention belongs to the technical field of data security management, and provides an operation and maintenance audit management system and method, and the system comprises a behavior control module which is used for carrying out the compliance detection of an operation and maintenance operation after receiving an operation and maintenance request initiated by any operation and maintenance terminal, and blocking the execution of the operation and maintenance request when the compliance detection result is that the operation and maintenance operation is abnormal; the auditing module is used for acquiring key information corresponding to all the operation and maintenance operations, adding marking information to the abnormal operation and maintenance operations, receiving auditing suggestions added to the abnormal operation and maintenance operations by an auditing terminal, and generating an auditing report according to the key information, the marking information and the auditing suggestions; the management module is used for performing account management, authentication management, authorization management and workflow management on the operation and maintenance terminal; and the storage module is used for carrying out classified storage on the operation and maintenance whole-process data containing the compliance detection result, the key information, the mark information and the auditing opinions. According to the scheme, the accuracy, reliability and safety of the operation and maintenance auditing link are improved.

The application discloses a dynamic environment self-adaptive control method, device, equipment, medium and program product, and relates to the field of edge computing. The method comprises the following steps: determining a prediction result inference mode of the next behavior according to environment perception data in a shared cache and running state data of a to-be-controlled device. If the behavior prediction stops updating, a behavior prediction result stop updating identifier parameter is cached in the shared cache as the behavior prediction result. If the behavior prediction mode is adopted, different data elements of historical behavior data and behavior prediction data read from the shared cache are determined, and the final behavior prediction result is determined according to the behavior difference data and the historical behavior data. The application can solve the problems of poor real-time performance and large resource demand in related technologies, effectively reduce the response delay of behavior control of intelligent entity devices or virtual objects, and reduce the required computing resources and storage resources in the control process.

The invention discloses a model optimization method and a related device, which can be applied to automatic driving, auxiliary driving, intelligent traffic, traffic simulation, vehicle-mounted scenes and the like. Perception data of the target object is obtained, an interpretation information prompt text is obtained, and the interpretation information prompt text is used for indicating the content understanding model to output the text content meeting the expectation. And outputting an object behavior control signal of the target object and decision explanation information matched with the explanation information prompt text through a content understanding model according to the perception data and the explanation information prompt text. If the action executed by the target object based on the object behavior control signal does not meet the preset target, that is, the object behavior control signal cannot control the target object to execute the correct action to cause avoidance failure, which link has a problem can be determined based on the decision interpretation information, so that the avoidance failure is avoided. Therefore, the content understanding model is adjusted more accurately and conveniently based on the decision interpretation information, and the performance of the content understanding model is improved.

An autonomous mobile robot includes a drive system supporting the robot above a surface, a sensor system configured to generate a signal indicative of a position of the robot on the surface, and a controller operably connected to the drive system and the sensor system. The drive system is operable to navigate the robot around the surface. The controller is configured to execute the instructions to operate, including establishing a behavioral control zone on the surface, in response to establishing the behavioral control zone on the surface, controlling the drive system to manipulate the robot to a location of the behavioral control zone on the surface, and manipulating the robot around the surface using the drive system, and initiate a behavior in response to determining that the robot approaches the behavior control region based on the signal indicative of the position of the robot.

The application discloses a kind of based on behavior control's bionic robot action control method, it is related to technical bionic robot control field, including the following steps: establishing global terrain coordinate system, completing multi-sensor calibration, robot starts autonomous navigation task, vision sensor starts to collect surrounding environment image;Image is handled, and the color, texture feature in image is extracted;Interference object identification module identifies the interference object therein, and extracts its feature information;Interference index analysis module calculates interference index according to the feature information of interference object;Terrain environment complexity evaluation module real-time collection terrain environment information, evaluates the complexity of terrain environment;Action control decision module comprehensively interference index and terrain environment complexity evaluation result, makes action control decision, and sends control instruction to motion execution mechanism, the application solves the problem of bionic robot in complex environment motion intelligence and safety.

The behavior control system includes: a behavior recognition unit that recognizes a behavior of a user; a difficulty estimation unit that estimates the difficulty of a question when the behavior of the user is recognized as the question; and a behavior specifying unit that, when the score corresponding to the difficulty level is equal to or greater than a threshold value, specifies, as behaviors to be executed, a behavior that feels happy to the question asked by the user and a behavior that answers the question.

This invention relates to the field of distributed computing technology, and in particular to a unified registration and scheduling system for AI agent capabilities in edge-cloud collaboration, comprising: a dynamic behavior mapping module for capturing client interaction behavior features and mapping them to behavior control topology, performing path adjustment when deviations occur, and registering the control behavior to a unified MCP capability center; a semantic feature compression module for dimensionality reduction and compression of the original multimodal data stream to generate low-dimensional semantic feature stubs; an asynchronous state alignment module for converting feature stubs into asynchronous stateless message streams and reconstructing context mirror data on the cloud side; an inference stream scheduling module for generating inference stream scheduling strategies based on multi-dimensional states; a thought chain flow control module for dynamically truncating the streaming output of the large model according to the strategy and extracting core control segments and confidence levels; and a residual collaborative execution module for sending the core control segments to the edge for residual logic completion, driving the topology to execute control behaviors.

The application discloses a kind of unmanned passenger elevator car driving behavior control method, equipment and medium, it is related to passenger elevator car technical field, solve the problem that current unmanned passenger elevator car corresponding driving behavior exists security risk, driving behavior control method includes: step S1, set the driving rule of unmanned passenger elevator car, unmanned passenger elevator car executes driving operation according to driving rule;Step S2, the driving behavior data of unmanned passenger elevator car of execution driving operation is collected when collecting time node;Step S3, according to driving behavior data, the driving behavior of unmanned passenger elevator car is analyzed;Step S4, according to behavior control signal, the safety control of unmanned passenger elevator car is carried out, the application realizes the accurate analysis of unmanned passenger elevator car corresponding driving behavior, and realizes the safety control to driving behavior.

The purpose of the present invention is to output an appropriate response in accordance with the state of a user. The behavior control system includes: a recognition unit that recognizes a state of a user on the basis of detection information detected from the user; and an output control unit that causes an electronic device provided with the article generation model to output a response to the user on the basis of the state of the user recognized by the recognition unit.

An object of the invention is to optimize the behavior of a vehicle. A control apparatus is a control apparatus that controls a behavior of a vehicle, and includes a control unit that executes, when slip of a wheel occurs due to a driving force, a first control of eliminating the slip and a second control of generating a larger braking force, as compared to the first control, at the wheel at which the slip is occurring. The control unit automatically executes the second control in response to the behavior of the vehicle.

A virtual object behavior determination method and apparatus, and an electronic device. The method comprises: if the position of a target virtual object and a first virtual item satisfy a preset condition, acquiring, from a preset database, behavior data corresponding to the first virtual item, wherein the behavior data comprises a plurality of game behaviors and the use probability corresponding to each game behavior; determining a target game behavior from the behavior data corresponding to the first virtual item, and controlling the target virtual object to execute the target game behavior in a game scene to obtain a target game result; and on the basis of the target game result, adjusting the use probability corresponding to each game behavior in the behavior data corresponding to the first virtual item in the preset database. In the method, on the basis of the game result generated when the target virtual object executes the target game behavior, the use probability corresponding to a game behavior in the preset database is adjusted in real time, so that a game behavior of the target virtual object determined on the basis of the preset database is more adapted to a game scene, thereby improving the combat power and the degree of personification of the target virtual object.

This invention provides a control device that reduces system costs by using message data in a distinctive format and controls in-vehicle equipment appropriately according to the vehicle's condition using a table. [Solution] The control device 10 includes a state conversion unit that inputs message data including a first state representing a basic vehicle state and a second state representing other vehicle states; a first storage unit that stores a first table which defines the control content to be performed on multiple control targets for each of the multiple first states that the vehicle can take; a behavior control unit that outputs information regarding the control to be performed on multiple control targets based on the first state and the first table; a second storage unit that stores a second table which shows information for changing the control content defined in the first table; and a second behavior determination unit, an additional behavior determination unit, and an additional control unit that change the control information output by the behavior control unit based on the second state and the second table when the message data includes a second state.

Selectively controllable apparatus for insertion into an ear canal, and related methods of use and operation for behavioral control. In one embodiment, the apparatus includes a body configured for insertion into an ear canal. In one variant, the body includes one or more thermal mechanisms which enable selective increase or decrease of temperature of at least portions of the ear canal so as to implement behavioral control of the user, such as to mitigate cravings for food, alcohol, narcotics, or other potentially deleterious substances. In one variant, a mild nausea or pre-nausea condition is created within the user according to a time-temperature profile so as to induce the aforementioned behavioral modification.

The invention discloses a humanoid robot controller training method, a humanoid robot controller control method and a humanoid robot controller training device. A two-stage training framework is adopted, and in the first stage, a reinforcement learning algorithm is adopted to independently train a plurality of single-behavior controllers which are specially used for different sports skills (such as walking and standing); then, the capabilities of the single-behavior controllers are integrated into a unified multi-behavior controller through a behavior distillation method, so that the unified multi-behavior controller has the capability of autonomously switching skills according to states. And in the second stage, in order to improve the robustness of the multi-behavior controller in a complex environment, a task environment for simulating various use terrains is constructed, and reinforcement learning fine tuning is performed on the controller in parallel in the environment, so that a controller capable of adapting to the complex terrains and realizing multi-skill smooth switching is finally obtained. The adaptive capacity of the humanoid robot controller and the reliability of practical application can be improved. The robot can be widely applied to the technical field of robots.

The application provides a virtual object control method and device and a storage medium, relates to the technical field of Internet, can be applied to various scenes such as cloud technology, artificial intelligence, intelligent transportation and auxiliary driving, and comprises the following steps: obtaining an object behavior tree of a target virtual object in a target game; a single node in the object behavior tree can perform data transmission with an AI system data center of the target game, and different nodes perform data communication through the AI system data center; through the object behavior tree, state information and environment information of the target virtual object in a virtual environment of the target game are obtained; in the case that an event triggering condition is reached, a corresponding target virtual event is triggered in the virtual environment, and a target behavior sub-tree corresponding to the target virtual event in the object behavior tree is activated; and the behavior of the target virtual object is controlled based on the target behavior sub-tree and the AI system data center. The application can effectively improve the flexibility of virtual object behavior configuration and behavior control.

The application discloses a kind of dimension self-adapting human behavior prediction method and equipment, the method first acquires the D-dimensional time series containing human behavior, carries out modal decomposition processing, obtains each dimension mode.Secondly, for each mode, the internal relationship between the implied state, activity contribution and observation event is constructed based on the dynamics equation.Then estimate each parameter of the dynamics equation, and construct total parameter set.Finally, the prediction sequence of each mode is inferred based on the total parameter set, and is reconstructed as D-dimensional time series, realize the prediction of human behavior.In the equipment, the central processing module processes the human behavior data collected by the perception module, the abnormal behavior control interaction module alarms, the communication module is used to send the abnormal data back to the personal computer end, and the data is transmitted to the storage module for saving when power failure or network interruption.The application does not need prior knowledge when carrying out human behavior prediction, low cost and high accuracy.

The present disclosure belongs to the field of blockchain technology, and particularly relates to a method and system for coordinating the correlation of multiple task stacks based on function frames. The control method includes: obtaining a user request, wherein the user request includes the user's processing action on the declaration document; generating a function frame corresponding to the processing action based on the user request; adding the function frame to a pre-set task stack, and sequentially executing the processing actions on the declaration document corresponding to all function frames in the task stack in the order of the task stack. The present disclosure adopts a task frame + freeze frame mode, and the freeze and unfreeze logic is programmable. The operating state of the stack is controlled through frame behavior; it simplifies the logic of the stack itself, solves the correlation coordination between multiple stacks, and effectively avoids the conflict problem between ledger operations and organizational operations.

This application discloses a leader-based UAV swarm behavior control method, system, and device, relating to the field of UAV control technology. The method uses control force parameters and time-varying control parameters to control the behavior of a leader UAV, expanding the traditional fixed parameter model to a time-varying parameter model. By sending time-varying control parameters to control the behavior of follower UAVs, the behavior of the UAV swarm is controlled, enabling distributed control. This reduces communication resource usage and effectively enhances the scalability of the UAV swarm.

And the robot can execute proper behaviors aiming at the user behaviors. To this end, a behavior control system includes: an emotion determination unit that determines an emotion of a user or an emotion of a robot; and a behavior determination unit that generates behavior content of the robot on the basis of a conversation function that causes the user to converse with the robot, the behavior of the user and the emotion of the user or the emotion of the robot, and determines the behavior of the robot corresponding to the behavior content, the emotion determination unit determining the emotion of the user in accordance with a specific map.

The invention discloses a ship lockage simulation method of self-adaptive time step length in a digital twinning scene, and belongs to the technical field of digital twinning and simulation. The method comprises the following steps: collecting and preprocessing ship motion state, ship lock structure and navigation rule data; a system architecture comprising a simulation layer, a control layer and a rule layer is constructed, the simulation layer adopts a multi-level physical engine cooperative computing mechanism, high-precision three-dimensional geometric modeling and real-time dynamic simulation are combined, and a self-adaptive time step control algorithm is introduced to dynamically adjust a simulation step in a key area so as to improve the precision; the control layer supports multi-ship-type dynamic parameter configuration through a modular ship behavior control model library; the rule layer drives navigation logic control through a rule engine, and flexibly executes rules such as single-line and double-line lockage and priority scheduling. According to the method, the problem of mold penetration caused by inaccurate collision detection in the prior art is effectively solved, and the universality, the flexibility and the intelligent level of multi-ship-type and multi-rule scenes are improved.

The behavior control system includes: an emotion determination unit that determines an emotion of a user or an emotion of a robot; and a behavior determination unit that generates behavior content of the robot for the behavior of the user and the emotion of the user or the emotion of the robot on the basis of a dialogue function that causes the user to dialogue with the robot, and determines the behavior of the robot corresponding to the behavior content. The behavior determination unit is provided with: an image acquisition unit capable of capturing an image of an athletic space in which a specific athletic can be implemented; and a competitor emotion analysis unit that analyzes the emotions of a plurality of competitors that are performing competitions in the competitive space captured by the image acquisition unit, and determines the behavior of the robot on the basis of the analysis results of the competitor emotion analysis unit.

A behavior determination unit determines, as a behavior of an avatar, any one of plural types of avatar behaviors including performing no operation by using at least one of a user state, a state of electronic equipment, an emotion of a user, or an emotion of an avatar representing an agent for having a dialogue with the user, and a behavior determination model at a predetermined timing; and a behavior control unit that displays the avatar in an image display region of the electronic equipment, in which the avatar behaviors include provision of advice on health to the user, and in a case where the behavior determination unit determines, as the behavior of the avatar, to provide advice on health to the user, the behavior determination unit autonomously determines a behavior corresponding to a health condition of the user based on a parameter representing the health condition of the user.

This invention discloses a smart pet ball based on behavior recognition and adaptive reward interaction, and its control method, belonging to the field of smart pet supplies technology. The smart pet ball includes a spherical shell, a drive mechanism, a control module, a posture detection module, an obstacle avoidance detection module, a reward delivery module, an interactive feedback module, a power supply module, and a communication module. The control module receives detection data from the posture detection module and the obstacle avoidance detection module, and controls the drive mechanism to perform rolling, bouncing, turning, stopping, or escape actions based on the ball's motion state, the external environment state, and the pet's interactive behavior. When preset conditions are met, the control module releases a fixed amount of pet food, and the control module outputs light, sound, or vibration feedback. This invention can form a closed loop between motion interaction and reward delivery, and automatically adjust the interaction mode according to the pet's touch frequency, chasing duration, collision state, or stress behavior characteristics, thereby improving the pet's interactive enthusiasm, training effect, and emotional soothing ability when alone.

The application discloses a model-free adaptive control method based on a 4D printing crawling robot, and comprises the following steps: a step of establishing a dynamic linearization data model; a step of calculating the value of the pseudo partial derivative at the current time by using a pseudo partial derivative estimation algorithm and a model-free adaptive controller; and a step of calculating the input signal value at each time by using the model-free adaptive control algorithm, and realizing step control and behavior control of an executing device of the 4D printing crawling robot by using input and output data of the model-free adaptive control algorithm. According to the application, the data-driven control of the 4D printing soft crawling robot can be realized, and the accurate behavior control and step control of the bidirectional crawling robot can be realized.

There is provided a behavior control system including: an emotion determination unit that determines an emotion of a user or an emotion of a robot; and a behavior determination unit that generates behavior content of the robot for the behavior of the user and the emotion of the user or the emotion of the robot on the basis of a dialogue function that causes the user to dialogue with the robot, determines the behavior of the robot corresponding to the behavior content, and determines the behavior of the robot according to the behavior content. The behavior determination unit executes: a process of reading a learning textbook including a textbook; a process of creating a question and setting the question to the user on the basis of the set target standard score and the read learning material; and a process of creating a new question and setting a question to the user on the basis of a standard score higher than the target standard score and the read learning textbook in a case where an answer to the question set to the user by the user is correct.

Method for controlling the activation (41) of a service function (23) depending on the usage behavior of a user of an electric vehicle (10), wherein a request (29) to activate (41) the service function (23) is received by a control interface (28) of a service facility (24) which provides the service function (23), wherein an identification feature (12) which is assigned to the electric vehicle (10) and for which the activation (41) is to take place is specified, and if the requested service (23) is unlocked, the service function (23) is activated by the service facility (24), characterized by the fact that Prior to the request for activation (41) by a computing device (26) at least one energy exchange (22) of electrical energy (14) between the electric vehicle (10) and a respective electric charging station (13), an energy class (21) and an energy quantity (18) of the exchanged energy (14) are recorded, wherein the energy class (21) indicates a technology of an energy source (20) which was used to generate the exchanged energy, and the technology indicates at least one of the following energy classes (21): nuclear power, hydropower, wind power, renewable energy, coal power, and an addition value (33) is assigned to the respective energy exchange (22) according to a predetermined evaluation rule (32) depending on the recorded energy class (21) and the recorded energy quantity (18), and the addition value (33) is added to a meter reading (35) assigned to the identification feature (12) in a data storage device (34), wherein the user's usage behavior with regard to the energy source used (20) is linked in such a way that the service function (23) is activated more easily the more often an energy source (20) of a certain technology is used and this is quantified by the evaluation rule (32) by issuing different addition values ​​(33) for the same value of energy quantity (18), depending on the energy class used (21), and the technical coupling between an energy exchange (22) at the at least one charging station (13) on the one hand and a control of the activation (41) of the service function (23) at the control interface (28) of the service facility (24) on the other hand is established by the requirement (36) is described by corresponding request data generated by the user, and the requirement (36) identifies the service function (23) and specifies the identification feature (12), and the service facility (24) for activating the service function (23) requires a threshold value (37) dependent on the service function (23) with respect to the meter reading (35) of the identification feature (12) and for this purpose transmits a request with respect to the meter reading (35) as a booking request with corresponding booking data specifying the threshold value (37) to a control system (25) which has the computing device (26) for recording the energy class (21) and the energy quantity (18) via the control interface (28), and The service function (23) is only activated if the meter reading (35) is greater than the threshold value (37) that depends on the service function (23).

The application provides a game role behavior control method and device and electronic equipment; wherein the method comprises: obtaining current state data of a target game; inputting the current state data into a pre-trained machine learning model to obtain a first output result; wherein the first output result comprises probabilities corresponding to a plurality of preset behavior operations; obtaining a specified number of historical output results of the machine learning model; inputting the first output result and the historical output result into a pre-trained conditional random field model to obtain a target behavior operation. In this way, the machine learning model and the conditional random field model are combined, the machine learning model and the conditional random field model can both establish a relationship between a state and a behavior operation, the conditional random field model can also establish a time sequence relationship between behavior operations, the intelligent degree of the game AI can be high, and meanwhile, the model structure is simple and easy to converge, and has strong applicability.