Monotonic solution concepts in coevolution

GECCO 2005 - Genetic and Evolutionary Computation Conference

Volumn , Issue , 2005, Pages 499-506

  Ficici, Sevan G ^a  

^a BRANDEIS UNIVERSITY   (United States)

Author keywords

Coevolution; Monotonic progress; Solution concepts

Indexed keywords

GAME THEORY; OPTIMIZATION;

COEVOLUTION; MONOTONIC PROGRESS; SOLUTION CONCEPTS;

EVOLUTIONARY ALGORITHMS;

EID: 32444443842     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1068009.1068093     Document Type: Conference Paper

References (31)

1. C. Adami. What is complexity? BioEssays, 24(12): 1085-1094, 2002.
2. P. J. Angeline and J. B. Pollack. Competitive environments evolve better solutions for complex tasks. In S. Forrest, editor, Proceedings of the Fifth International Conference on Genetic Algorithms, pages 264-270. Morgan Kaufmann, 1993.
3. J. P. Crutchfield. The calculi of emergence: Computation, dynamics and induction. Physica D, 75(1-3):11-54, 1994.
4. P. Darwen and X. Yao. Automatic modularization by speciation. In T. Fukuda et al., editors, Proc. of the 1996 IEEE International Conference on Evolutionary Computation, pages 88-93. IEEE Press, 1996.
5. E. D. de Jong. The incremental pareto-coevolution archive. In K. Deb et al., editors, Proc. 2004 Genetic and Evolutionary Computation Conference, LNCS 3102, pages 525-536. Springer, 2004.
6. E. D. de Jong. The maxsolve algorithm for coevolution. In U.-M. O'Reilly, editor, Proc. 2005 Genetic and Evolutionary Computation Conference. ACM, 2005.
7. K. A. De Jong. Are genetic algorithms function optimizers? In R. Männer and B. Manderick, editors, Parallel Problem Solving from Nature II, pages 3-13. Elsevier, 1992.
8. K. A. De Jong. Genetic algorithms are NOT function optimizers. In L. D. Whitely, editor, Foundations of Genetic Algorithms 2(FOGA), pages 5-18. Morgan Kaufmann, 1993.
9. S. G. Ficici. Solution Concepts in Revolutionary Algorithms. PhD thesis, Brandeis University, 2004.
10. S. G. Ficici and J. B. Pollack. A game-theoretic memory mechanism for coevolution. In Cantü-Paz et al., editors, 2003 Genetic and Evolutionary Computation Conference, pages 286-297. Springer, 2003.
11. C. M. Fonseca and P. J. Fleming. An overview of evolutionary algorithms in multiobjective optimization. Evolutionary Computation, 3(1):1-16, 1995.
12. W. Fontana. Algorithmic chemistry. In Langton et al. [18], pages 159-209.
13. H. Freund and R. Wolter. Evolution of bit strings: Some preliminary results. Complex Systems, 5:279-298, 1991.
14. I. Harvey. Cognition is not computation: Evolution is not optimisation. In W. Gerstner et al., editors, Proc. of the 7th Int. Conf. on Artificial Neural Networks, pages 685-690. Springer-Verlag, 1997.
15. T. Hashimoto and T. Ikegami. Emergence of net-grammar in communicating agents. Bio Systems, 38(1):1-14, 1996.
16. T. Ikegami. From genetic evolution to emergence of game strategies. Physica D, 75(1-3):310-327, 1994.
17. J. F. Kolen and J. B. Pollack. The observer's paradox: Apparent computational complexity in physical systems. Journal of Experimental and Theoretical Artificial Intelligence, 7:253-277, 1995.
18. C. Langton et al., editors. Artificial Life II. Addison-Wesley, 1992.
19. R. E. Lenski, C. Ofria, T. C. Collier, and C. Adami. Genome complexity, robustness and genetic interactions in digital organisms. Nature, 400:661-664, August 1999.
20. K. Lindgren. Evolutionary phenomena in simple dynamics. In Langton et al. [18], pages 295-312.
21. S. Luke and R. P. Wiegand. When revolutionary algorithms exhibit evolutionary dynamics. In A. Barry, editor, 2002 Genetic and Evolutionary Computation Conference Workshop Program, pages 236-241, 2002.
22. J. Maynard-Smith. Evolution and the Theory of Games. Cambridge University Press, 1982.
23. S. Nolfi and D. Floreano. Co-evolving predator and prey robots: Do 'arm races' arise in artificial evolution? Artificial Life, 4(4):311-335, 1998.
24. M. Potter and K. De Jong. Cooperative coevolution: An architecture for evolving coadapted subcomponents, Evolutionary Computation, 8(1):l-29, 2000.
25. T. S. Ray. Evolution, complexity, entropy and artificial reality. Physica D, 75(1-3):239-263, 1994.
26. C. D. Rosin and R. Belew. A competitive approach to game learning. In A. Blum and M. Kearns, editors, Proc. of the Ninth Annual A CM Conf. on Computational Learning Theory, pages 292-302. ACM Press, 1996.
27. L. M. Schmitt. Theory of revolutionary genetic algorithms. In M. Guo and L. T. Yang, editors, Int. Symp. on Parallel and Distributed Processing and Applications, volume 2745 of LNCS, pages 285-293. Springer, 2003.
28. K. Sims. Evolving 3d morphology and behavior by competition. In R. A. Brooks and P. Maes, editors, Artificial Life IV, pages 28-39, MIT Press, 1994.
29. T. Taylor. Creativity in evolution: Individuals, interactions and environments. In P. J. Bentley and D. W. Corne, editors, Creative Evolutionary Systems, pages 79-108. Morgan Kaufmann, 2001.
30. L. van Valen. A new evolutionary law. Evolutionary Theory, 1:1-30, 1973.
31. R. A. Watson and J. B. Pollack. Revolutionary dynamics in a minimal substrate. In L. Spector et al., editors, Proc. of the 2001 Genetic and Evolutionary Computation Conference, pages 702-709, 2001.