Performance evaluation of an evolutionary method for RoboCup soccer strategies

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4020 LNAI, Issue , 2006, Pages 616-623

  Nakashima, Tomoharu ^a   Takatani, Masahiro ^a   Udo, Masayo ^a   Ishibuchi, Hisao ^a   Nii, Manabu ^b  

^a Osaka Prefecture University   (Japan)

^b UNIVERSITY OF HYOGO   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

CHROMOSOMES;

ACTION RULES; CROSSOVER AND MUTATION; ES TYPES; EVOLUTIONARY METHOD; INTEGER STRINGS; ROBOCUP SOCCER; UPDATE SCHEMES;

SPORTS;

EID: 37249040130     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11780519_61     Document Type: Conference Paper

References (7)

1. RoboCup official page, http://www.robocup.org
2. T. Nakashima, M. Udo, H. Ishibuchi, "A Fuzzy Reinforcement Learning for a Ball Interception Problem," RoboCup 2003: Robot Soccer World Cup VII, in press.
3. K. Chellapilla, and D.B. Fogel, "Evolving Neural Networks to Play Checkers Without Relying on Expert Knowledge", IEEE Trans. on Neural Networks, Vol.10, No.6, pp.1382-3191, 1999.
4. K. Chellapilla, and D.B. Fogel, "Evolving an Expert Checkers Playing Program Without Using Human Expertise", IEEE Trans. on Evolutionary Computation, Vol.5, No.4, pp. 422-428, 2001.
5. S. Luke and L. Spector, "Evolving Teamwork andCoordination with Genetic Programming" , Proceedings of the First Annual Conference on Genetic Programming, pp.150-56, 1996.
6. Back, T.: Evolutionary Algorithms in Theory and Practice. Oxford University Press, New York, NY (1996)
7. UvA Trilearn team, http://carol.science.uva.nl/~jellekok/robocup/ index_en.html