An empirical comparison of non-adaptive, adaptive and self-adaptive co-evolution for evolving artificial neural network game players

2006 IEEE Conference on Cybernetics and Intelligent Systems

Volumn , Issue , 2006, Pages

  Yau, Yi Jack ^a   Teo, Jason ^a  

^a UNIVERSITI MALAYSIA SABAH   (Malaysia)

Author keywords

Adaptation; Co evolution; Evolutionary artificial neural networks; Game AI; Self adaptation

Indexed keywords

ADAPTIVE SYSTEMS; EVOLUTIONARY ALGORITHMS; GAME THEORY; PARAMETER ESTIMATION; STABILITY; CYBERNETICS; INTELLIGENT SYSTEMS;

EVOLUTIONARY ARTIFICIAL NEURAL NETWORKS; GAME PLAYERS; SELF ADAPTATION;

NEURAL NETWORKS;

ADAPTATION; CO-EVOLUTION; EVOLUTIONARY ARTIFICIAL NEURAL NETWORKS; GAME AI; SELF ADAPTATION;

EID: 42749108837     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCIS.2006.252234     Document Type: Conference Paper

References (15)

1. P.J. Angeline, "Adaptive and self-adaptive evolutionary computation," M., P., Attiliouzel, Y.,Marks, R., D., F., Fukuda, T. (eds), Computational Intelligence, A Dynamic System Perspective. IEEE Press, pp 152-161, 1995.
2. P.J. Angeline, "Two self-adaptive crossover operators for genetic programming", P.J. Angeline, K.E. Kinnear (eds), Advances in Genetic Programming II, MIT Press, 1996, pp 89-110.
3. K. Chellapilla and D.B. Fogel, "Evolution, neural networks, games, and intelligence", Proceedings of the IEEE, vol.87, no.9, 1999, pp 1471-1496.
4. K. Chellapilla and D.B. Fogel, "Evolving an expert checkers playing program without using human expertise", IEEE Transaction on Evolutionary Computation, vol.5, no.4, pp 422-428, 2001.
5. D.B. Fogel, "Using evolutionary programming to construct neural networks that are capable of playing Tic-Tac-Toe", Proceedings of 1995 IEEE International Conference on Neural Networks, San Francisco, CA, 1993, pp 875-880.
6. N. Franken, and A.P. Engelbrecht, "Evolving game-playing agents", Proceedings SAICSIT 2003 Annual Conference of the South African Institute of Computer Scientists and Information Technologists, 2003, pp 102-110.
7. R. Hinterding, Z. Michalewicz and A.E. Eiben, "Adaptation in evolutionary computation: a survey", Evolutionary Computation, 1997, IEEE International Conference on 13-16 April 1997, pp 65-69.
8. G. Kendall and G. Whitwell, "An evolutionary approach for the tuning of a chess evaluation function using population dynamics", 2001 IEEE Congress on Evolutionary Computation (CEC 2001), 2001, pp. 995-1002.
9. A. Lubberts and R. Miikkulainen, "Co-evolving a Go-playing neural network", R. Belew and H. Juille (eds), Coevolution: Turning Adaptive Algorithm upon Themselves, 2001, pp 14-19.
10. L. Messerschmidt and A.P. Engelbrecht, "Learning to play games using a PSO-based competitive learning approach", Proceedings of the 4th Asia-Pacific Conference on Simulated Evolution and Learning, 2002, Singapore.
11. Z. Michalewicz and D.B. Fogel, How to Solve It: Modern Heuristics 2nd edn, Springer, Berlin Heidelberg New York, 2004.
12. D. Moriaty and R. Miikkulainen, "Discovering complex Othello strategies through evolutionary neural networks", Connection Science, vol. 7, no. 3-4,1995, pp 195-207.
13. N. Richard, D. Moriaty, P. McQuesten, R. Miikkulainen, "Evolving neural networks to play Go", 7th International Conference on Genetic Algorithms, 1998.
14. R. Storn, "System design by constraint adaptation and differential evolution", IEEE Transaction on Evolutionary Computation, vol. 3, no. 1, 1999, pp 22-34.
15. Y.J. Yau and J. Teo, "Co-evolutionary Versus Canonical Algorithms for Evolving Game AI", International Conference on Intelligent Systems (ICIS 2005), CD Proceedings, Kuala Lumpur, December 2005.