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Title:
Gemini - learning cooperative behaviors without communicating
Author:
Masayuki Ohta: Tokyo Institute of Technology, Japan
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Year:
1999
Conference:
RobocCup-99 Team Descriptions. Simulation League
Issue:
004
Article no.:
008
Pages:
36-39
No. of pages:
4
Publication type:
Abstract and Fulltext
Published:
1999-12-15
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Series:
Linköping Electronic Articles in Computer and Information Science
ISSN (online):
1401-9841
Publisher:
Linköping University Electronic Press; Linköpings universitet
This paper describes the design of Gemini a client program for SoccerServer. The goal of Gemini is learning cooperative behaviors without direct communication in multi-agent environment. With recent implementation; it can select the best strategy against opponent; statistically.
RobocCup-99 Team Descriptions. Simulation League
Author:
Masayuki Ohta
Title:
Gemini - learning cooperative behaviors without communicating
References:
[1] M.Ohta and T.Ando \Cooperative Reward in Reinforcement Learning" Proc. of 3rd JSAI RoboMech Symposia pages 7-11 April 1998.
[2] Grefenstette, John.J. \Credit Assignment in Rule Discoverry Systems Based on Genetic Algorithms" Machine Learning, Vol.3 pages 225-245 1988.
[3] Kaelbling L. P., Littman M. L. and Moore A. W. \Reinforcement Learning: A Survey" Journal of Arti cial Intelligence Research 4, pages 237-285 1996.
[4] Kimura H., Yamamura M. and Kobayashi S. \Reinforcement Learning in Partially Observable Markov Decision Processes: A Stochastic Gradient Method" Journal of Japanese Society for Arti cial Intelligence, Vol.11, No.5 papges 761-768 1996
RobocCup-99 Team Descriptions. Simulation League
Author:
Masayuki Ohta
Title:
Gemini - learning cooperative behaviors without communicating
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