Online adjustment of the AI's strength in a fighting game using the k-nearest neighbor algorithm and a game simulator

This paper proposes a method for online adjustment of the AI's strength in a fighting game. The adjustment aim is that of maintaining the AI's strength slightly above its opponent's level. The proposed method adopts the k-nearest neighbor algorithm for predicting the opponent's n...

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Bibliographic Details
Published in2014 IEEE 3rd Global Conference on Consumer Electronics (GCCE) pp. 494 - 495
Main Authors Nakagawa, Yuto, Yamamoto, Kaito, Thawonmas, Ruck
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2014
Subjects
AI's strength
Artificial intelligence
Computers
Educational institutions
Entertainment industry
fighting games
Games
k-nearest neighbor
Laboratories
online adjustment
Prediction algorithms
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Summary:This paper proposes a method for online adjustment of the AI's strength in a fighting game. The adjustment aim is that of maintaining the AI's strength slightly above its opponent's level. The proposed method adopts the k-nearest neighbor algorithm for predicting the opponent's next action and uses this information together with a game simulator for determining the next action of the AI, leading to slightly winning scores against the opponent. The proposed method is evaluated on a fighting-game used at the fighting game AI competition organized by the authors since 2013. Evaluation results confirm the effectiveness of the proposed method.
ISSN:2378-8143
2693-0854
DOI:10.1109/GCCE.2014.7031274