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Modeling method oriented to multi-agent synchronous gaming and action prediction system

A multi-agent, modeling method technology, applied in computational models, biological models, instruments, etc., can solve problems such as the inability to improve the game ability of the strategy model, achieve good practical application value, strong real-time performance, and improve the guiding role Effect

Active Publication Date: 2018-11-06
UNIV OF SCI & TECH OF CHINA
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Problems solved by technology

[0005] In view of this, the present invention provides a multi-agent synchronous game-oriented modeling method and action prediction system to solve the problem that existing modeling schemes cannot improve the game ability of the strategy model and have good real-time performance question

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  • Modeling method oriented to multi-agent synchronous gaming and action prediction system
  • Modeling method oriented to multi-agent synchronous gaming and action prediction system
  • Modeling method oriented to multi-agent synchronous gaming and action prediction system

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Embodiment Construction

[0048] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0049] Multi-agent synchronous game strategy, as an important content in real-time strategy games, has good application prospects in military, economic and other fields. Accurately giving the best actions of all participating units of one's own side in a given state is the whole decision-making the crux of the matter. In military deduction, timely adjustment of the offensive defense of one's own participating units and the dispatch of military supplies based o...

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Abstract

The invention provides a modeling method oriented to multi-agent synchronous gaming and an action prediction system. The modeling method comprises the steps that a state set and an action set of synchronous gaming problems are obtained; according to the characteristics of the synchronous gaming problems, gaming features and a feature coding method are designed; according to the gaming features andthe feature coding method, the state set and the action set are subjected to data preprocessing, and thus a basic feature graph and an action decision graph are obtained; a multi-scale feature fusionsynchronous gaming strategy model is established on the basis of a deep neural network; and according to the basic feature graph and the action decision graph, the synchronous gaming strategy model is trained layer by layer, thus the trained synchronous gaming strategy model is obtained, and the synchronous gaming strategy model has the high real-time performance while the gaming ability of the synchronous gaming strategy model is improved. The action prediction system realized based on the synchronous gaming strategy model is high in accuracy and real-time performance and has the good practical application value.

Description

technical field [0001] The invention relates to the field of machine games, and more specifically, relates to a modeling method and an action prediction system for multi-agent synchronous games. Background technique [0002] Machine game research on how to allow computers to simulate humans to play games is one of the most challenging research directions in the field of artificial intelligence. Among them, the simultaneous game problem (where participants act simultaneously) represented by real-time strategy games has become a research hotspot in the field of artificial intelligence. [0003] The task of multi-agent synchronous game strategy is to let the computer accurately give the best actions of all participating units. The current mainstream solutions are search methods and multi-agent reinforcement learning. The search method builds a search tree through state clustering and action clustering, and calculates the local optimal solution online; multi-agent reinforcemen...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/00
CPCG06N3/006
Inventor 王子磊陈鹏李厚强
Owner UNIV OF SCI & TECH OF CHINA
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