Motion determination model training method and device for virtual object, equipment and medium

A virtual object and model training technology, applied in the field of artificial intelligence, can solve the problems of weak confrontation ability, lack of robustness, single game strategy, etc., and achieve the effect of improving confrontation ability and robustness

Pending Publication Date: 2021-01-15
TENCENT TECH (SHENZHEN) CO LTD
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AI Technical Summary

Problems solved by technology

[0004] The technical problem in the above technical solution is that since the reward signal of the AI ​​in the above RL is a dense reward signal defined by the technician, the trained AI can only execute a single game strategy, resulting in the AI’s ability to fight against the game strategy. Weak, lack of robustness

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  • Motion determination model training method and device for virtual object, equipment and medium
  • Motion determination model training method and device for virtual object, equipment and medium
  • Motion determination model training method and device for virtual object, equipment and medium

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Embodiment Construction

[0041] In order to make the purpose, technical solution and advantages of the present application clearer, the implementation manners of the present application will be further described in detail below in conjunction with the accompanying drawings.

[0042] Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numerals in different drawings refer to the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with aspects of the present application as recited in the appended claims.

[0043] The technologies that may be used in the following embodiments of the present application are introduced below.

[0044]Artificial...

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Abstract

The invention provides a motion determination model training method and device for a virtual object, equipment and a medium, and belongs to the technical field of artificial intelligence. The method comprises the steps of determining a computing environment state of a virtual scene after a target duration based on a first environment state of the virtual scene; determining internal reward information according to the calculation environment state and the actual environment state of the first environment state at the next moment; adjusting parameters of the current action determination model according to the internal reward information; and in response to the fact that the current action determination model meets the first target condition, determining the current action determination modelas a trained motion determination model. According to the scheme, the motion output by the motion determination model can correspond to different game strategies, and the confrontation capacity and robustness of the virtual object on the game strategies are improved.

Description

technical field [0001] The present application relates to the technical field of artificial intelligence, in particular to a method, device, equipment and medium for training a virtual object's action determination model. Background technique [0002] With the development of artificial intelligence (AI) technology, AI has challenged top humans in various fields, and has approached the top level of human competition. For example, in the field of Go, Alpha Go defeated the world champion of Go, and in the field of games, Alpha Star defeated professional players of StarCraft II (a real-time strategy game) and so on. Currently, research on game AI issues has become a testing ground for exploring real-world general artificial intelligence. [0003] At present, for Multiplayer Online Battle Arena (MOBA), because MOBA games are affected by complex content such as lineup combinations, strategic goals, and tactical execution, reinforcement learning (Reinforcement Learning, RL) is usu...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A63F13/55
CPCA63F13/55
Inventor 杜雪莹石贝练振杰高一鸣陈光伟王亮付强
Owner TENCENT TECH (SHENZHEN) CO LTD
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