Comparison of several machine learning techniques in pursuit-evasion games

Hansjoerg (Jacky) Baltes*, Yongjoo Park

*此作品的通信作者

研究成果: 書貢獻/報告類型會議論文篇章

摘要

This paper describes the results of an empirical evaluation comparing the performance of five different algorithms in a pursuit and evasion game. The pursuit and evasion game was played using two robots. The task of the pursuer was to catch the other robot (the evader). The algorithms tested were a random player, the optimal player, a genetic algorithm learner, a k-nearest neighbor learner, and a reinforcement learner. The k-nearest neighbor learner performed best overall, but a closer analysis of the results showed that the genetic algorithm suffered from an exploration-exploitation problem.

原文英語
主出版物標題RoboCup 2001
主出版物子標題Robot Soccer World Cup V
頁面269-274
頁數6
出版狀態已發佈 - 2002 十二月 1
事件5th Robot World Cup Soccer Games and Conferences, RoboCup 2001 - Seattle, WA, 美国
持續時間: 2001 八月 22001 八月 10

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
2377 LNAI
ISSN(列印)0302-9743
ISSN(電子)1611-3349

其他

其他5th Robot World Cup Soccer Games and Conferences, RoboCup 2001
國家/地區美国
城市Seattle, WA
期間2001/08/022001/08/10

ASJC Scopus subject areas

  • 理論電腦科學
  • 電腦科學(全部)

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