Two Multi-Unit Artificial Intelligence Decision Modes in Video Games：A Comparison

Qisen Lin

doi:10.47297/taposatWSP2633-456909.20230402

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Two Multi-Unit Artificial Intelligence Decision Modes in Video Games：A Comparison

4卷第2期

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Two Multi-Unit Artificial Intelligence Decision Modes in Video Games：A Comparison
Two Multi-Unit Artificial Intelligence Decision Modes in Video Games：A Comparison
School of Information Engineering, Wuhan University of Technology,Hubei,Wuhan,P. R. China,430070
2023年4卷第2期页码：60-67
纸质出版日期： 2023 ，
DOI：10.47297/taposatWSP2633-456909.20230402

Full txt

(2023). Two Multi-Unit Artificial Intelligence Decision Modes in Video Games：A Comparison. 科技理论与实践（英文版）, 4(2), 60-67.

Qisen Lin. (2023). Two Multi-Unit Artificial Intelligence Decision Modes in Video Games：A Comparison. Theory and Practice of Science and Technology, 4(2), 60-67.
(2023). Two Multi-Unit Artificial Intelligence Decision Modes in Video Games：A Comparison. 科技理论与实践（英文版）, 4(2), 60-67. DOI： 10.47297/taposatWSP2633-456909.20230402.

Qisen Lin. (2023). Two Multi-Unit Artificial Intelligence Decision Modes in Video Games：A Comparison. Theory and Practice of Science and Technology, 4(2), 60-67. DOI： 10.47297/taposatWSP2633-456909.20230402.

摘要

Abstract

Using AI to manipulate game characters is already common and has been applied to various types of games. However

many current studies focus on AI operating a single role. In future online games

there will be a great demand to operate multiple units simultaneously for collaborative movement

and similar needs have already appeared in current MMORPG. In popular battle games nowadays

there is often a game mode where multiple players belonging to multiple factions engage in battles with each other. If AI needs to be deployed

multiple units need to be operated simultaneously to engage in combat. In response to this issue

two network architectures were proposed and trained and tested in a multiplayer game simulation environment. By comparing the training effects

one of the network structures known as “octopus- shape” is considered to be more effective and valuable for development. This result will contribute to the development of multi unit collaborative artificial intelligence in the future

helping to establish true AI games and real-world automated management systems.

关键词

Keywords

Artificial intelligenceReinforcementOnline gameNeural networkCooperative system

references

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