120 results about "Non-player character" patented technology

A multi-user video game with communications capabilities allows players to communicate with one another via simulated mail, leaflets and conversations. Different installations of the game on different discrete video game playing platforms may be unique or different depending upon random or other data available at the platform. For example, different installations may have different subsets of characters, different landscapes, or the like. Player characters from one virtual environment or village may visit another virtual environment or village and return home to his or her resident environment or village. Non-player characters may move from one virtual environment or village to another—thereby providing an ever-changing variety of characters. Communications between different game playing platforms can be provided via portable memory devices, portable game playing devices, or conventional communications means such as networks.

Providing dynamic learning for software agents in a simulation. Software agents with learners are capable of learning from examples. When a non-player character queries the learner, it can provide a next action similar to the player character. The game designer provides program code, from which compile-time steps determine a set of raw features. The code might identify a function (like computing distances). At compile-time steps, determining these raw features in response to a scripting language, so the designer can specify which code should be referenced. A set of derived features, responsive to the raw features, might be relatively simple, more complex, or determined in response to a learner. The set of such raw and derived features form a context for a learner. Learners might be responsive to (more basic) learners, to results of state machines, to calculated derived features, or to raw features. The learner includes a machine learning technique.

Each time a player character performs a boom triggering act, “1” is added to the corresponding act number counter provided for each non-player character. The value of each act number counter is periodically added to a boom value provided for each non-player character. When a boom value reaches an upper limit, the corresponding non-player character performs an act related to the boom triggering act performed by the player character. Thus, the act of each non-player character is changed in accordance with the act performed by the player character in the game world, which provides the player with a fresh feeling that the act performed by the player character set a trend in the game world.

A system and method are provided for transparently styling non-player characters (“NPCs”) in multiplayer video games such that it is difficult to distinguish between human players and computer-controlled NPCs. NPCs may be styled to resemble human players in terms of both player profile attributes and gameplay actions such that players may not recognize NPCs as non-human, computer-controlled players. Additionally, or alternatively, NPCs and/or human players may be presented with a limited set of profile attributes that may reduce or eliminate the ability to distinguish between human players and NPCs, one or more profile attributes may be “anonymized,” and/or the ability to view player profiles of human players and/or NPCs may be disabled altogether. In certain gameplay sessions including real and/or practice gameplay sessions, human players may be prompted to select from among a predetermined set of playable characters having predefined profile attributes.

The invention discloses a realization method of intelligent non-player characters in an interactive game, the method controls the intelligent behaviors of the non-player characters through a game engine at a server end, a network application programming interface containing JavaBot, a JavaBot bottom-layer processing unit, as well as client ends of a BDI reasoning unit. In addition, the invention also discloses an interactive game system to realize the method. The invention has the advantages that the game engine increases one layer of the game Agent unit, which can make the game developers work with AOP way when programming and processing NPC behaviors without considering the implementation details. Therefore, such the intelligent NPC realization system can be more helpful to express the intelligent behaviors of non-player characters in the game, as well as better support the application of intelligent technology in the game.

Techniques are disclosed for tracking physical play objects by virtual or non-player characters in an electronic game environment. More specifically, techniques are disclosed for enabling a game system to track a physical toy object, using tracking information to update the game state, and transmitting updated game state to the toy object and update the toy state. Additionally, a player is able to control the physical toy object, and use the physical toy object to play a game. The game system may track a remote-controlled toy, a handheld toy, or the player himself or herself. The virtual feedback to changes in the physical environment results in a more immersive game experience for the player.

Provided is a method of interacting with a non-player character in a virtual world. With a computer system, a user is granted access to an interface allowing the user to establish a friendship with a computer-controlled character. Such a friendship is established by adding the computer-controlled character to a list of friends associated with the user. The user is then granted access to a restricted portion of the virtual world that was not accessible to the user before the user entered the friendship request.

The embodiment of the invention discloses an NPC (Non-Player Character) behavior decision method. The method comprises the following steps of initializing attribute set information of an NPC; obtaining a triggering event of the NPC through a sensor; determining a willing target of the NPC according to the corresponding relationship between the triggering event and the willing target; finding the attribute set information matched with the willing target; generating at least willing target option according to the matched attribute set information; determining a behavior plan according to the willing target option and the willing target option weight; executing the behavior plan; and correcting the willing target of the NPC according to the feedback of the behavior plan. The NPC in the game can realize the artificial intelligence; and the thinking mode and the behavior action similar to the human are realized. The novelty and the interestingness of the game are enhanced, so that a game player can gain good game experience, and the game dependency of the player is enhanced.

Featured is a game applications programs, software, systems and methods that are such as to provide an interactive gaming experience for one or more game players by using speech recognition techniques in combination with interactive techniques and functionalities thereby as creating an interface that allows spoken words and/or phrases of a game player to initiate any one of a number of functionalities, actions or informational outputs in connection with the conduct of the game. Such methods, programs, and systems can further include creating an interface that allows a game player to initiate a function or action to be performed by the game player's character, to initiate a dialog or interaction between a player's character and a non-player character appearing in a game or to request information from a non-player character or about a phase of the game in general as part of the play of the game.

A predetermined special control point is added to an accumulated special control point in accordance with predetermined lapse of time up to a predetermined maximum accumulated value. An image display apparatus displays the accumulated special control point on the image display screen. The special control is executed in the case where the accumulated value of the special control point is more than an initial value when an instruction to execute special control is received on the basis of operations of the player. In this case, an action speed of a non-player character is caused to become slow with respect to that of a player character under the special control.

The embodiment of the invention provides a game action processing method and device. The method comprises the steps of acquiring the current game state and action space of a non-player character; inputting the current game state into a pre-trained reinforcement learning network model to obtain a reinforcement strategy, wherein the reinforcement strategy comprises a first selection probability of each game action; inputting the action space into a pre-trained auxiliary rule network model to obtain an auxiliary strategy, wherein the auxiliary strategy comprises a second selection probability ofeach game action; determining a target strategy according to the reinforcement strategy and the auxiliary strategy, wherein the target strategy comprises a target probability generated by each game action on the basis of the corresponding first selection probability and the corresponding second selection probability; screening out a target game action from the action space according to the targetprobability of each game action and controlling the non-player character to execute the target game action. The game action processing method and device can improve the game experience of players.

Methods and systems are disclosed herein for gate crashing computer-based games. In one embodiment, a method for playing a console-based game on a host player gaming system can include receiving a request from a host player to allow gate crashing in the game. In response to the request, information related to the game can be transmitted to a server computer. The server computer can forward the information to a remote gate crasher gaming system. A gate crasher can then view the information and submit a request to crash the game and control one of the non-player characters.

Embodiments of the present disclosure disclose a method and a device for predicting character behaviors of a non-player character in a game. The method includes receiving status data of a current game sent by a game client, the status data being used to indicate current status of a plurality of characters in the current game; obtaining a behavior order sequence related to the current game from a pre-established behavior order library based on the current status, wherein the behavior order sequence indicates a behavior execution order of the plurality of characters including both player characters and non-player characters; performing simulation on the plurality of characters by using a behavior prediction model in sequence according to the behavior execution order to obtain a simulation result; updating the behavior prediction model according to the simulation result to obtained an updated behavior prediction model; using the updated behavior prediction model to generate behavior information, the behavior information being used to indicate next behaviors of one or more of non-player characters among the plurality of characters; and sending the behavior information to the game client to control the behavior of the one or more non-player characters.

The invention discloses a training method and device for an intelligent game agent. The training method comprises the steps that an own state, an observation state and an output behavior of a player character are encoded to obtain player data, and an intelligent player agent is constructed; a pre-established initial NPC is adopted to perform interaction training on the intelligent player agent, and parameters corresponding to a player behavior strategy are updated according to parameters of the intelligent player agent after training; according to the parameters corresponding to the player behavior strategy, the trained intelligent player agent is adopted to perform interactive training on an intelligent NPC agent, and according to parameters of the trained intelligent NPC agent, parameters corresponding to a NPC behavior strategy are updated; and the parameters corresponding to the NPC behavior strategy is iteratively used for optimizing the parameters corresponding to the player behavior strategy, and the parameters corresponding to the NPC behavior strategy are optimized by using the parameters corresponding to the player behavior strategy until the NPC behavior strategy is stable. The problem that in the prior art, it is difficult to obtain the interactive data with a player in the non-player character training can be effectively solved, and the training effect of the intelligent non-player agent can be effectively improved.

The embodiment of the invention discloses a method and a device for path finding of a non-player character, a storage medium and a computer device. The method comprises the steps that a path finding request for path finding of a target non-player character NPC is received, wherein the path finding request comprises index information of the target NPC; according to the index information of the target NPC, the position of the target NPC in a game scene is acquired; according to the current position of a virtual character in the game scene and the position of the target NPC in the game scene, a pre-generated connected graph is selected as a grid map for path finding of the target NPC; and based on the grid map, path finding of the target NPC is performed. Compared with the prior art, the method for path finding of the non-player character is high in efficiency, and especially for games with complex scenes, the time cost of green hand players can be obviously saved.

The invention discloses a model training method applied to the field of artificial intelligence. The method comprises the steps: acquiring first state information corresponding to a first object and second state information corresponding to a second object; based on the first state information, obtaining first action information through a first to-be-trained battle network model; acquiring secondaction information through a second to-be-trained battle network model based on the second state information; based on the first state information, the second state information, the first action information and the second action information, obtaining a value expectation through a discrimination network model; and updating the model parameters of the first to-be-trained battle network model according to the value expectation to obtain a first battle network model. The invention further discloses an object control method and device based on the interactive application. According to the invention, cooperation and cooperation among a plurality of non-player characters can be realized, the operation difference between the non-player characters and a real player is reduced, and the fighting level of the non-player characters and the real player is improved.

The technical scheme of the present invention comprises an optimization method for artificial intelligence performing a task. The method comprises: using an atomic behavior to substitute the task performed by an artificial intelligence role; carrying out singulation processing on a single task behavior; deleting an associated behavior; and carrying out searching substitution and multitasking algorithm processing before task performing. Beneficial effects of the method disclosed by the present invention are that: complexity of artificial intelligence behaviors design is reduced, a high level of intelligence is maintained in overall behaviors of the NPC (Non Player Character), artificial intelligence is enabled to have a realistic substitution sense, and better gaming experience is brought to players.

By setting the player's recording medium in the game device, the continuity of the previous game and current game of the player is maintained, and the game parameter of a non-player character is set with a used recording medium. The game device (30) has a unit (S24) for conducting a first game in which a plurality of characters participate including a player character and a non-player character upon using a recording medium (20) having recorded thereon the number of playable games; a unit (S26) for recording the game parameter of the player character renewed with the first game on the recording medium and deducting the number of playable games; a unit (S53) for using the recording medium to set the game parameter of the non-player character in the second game when there is a remainder in the number of playable games in the recording medium; and a unit (S57) for using the recording medium to set the game parameter of the non-player character in the second game when there is no remainder in the number of playable games in the recording medium.