Measuring the dynamics of artificial evolution

Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

Volumn 2801, Issue , 2003, Pages 580-587

  Burtsev, Mikhail S ^a  

^a KELDYSH INSTITUTE OF APPLIED MATHEMATICS   (Russian Federation)

Author keywords

[No Author keywords available]

Indexed keywords

GENES; TRAJECTORIES; PHASE SPACE METHODS;

ARTIFICIAL EVOLUTION; DYNAMICAL SYSTEM; EVOLUTIONARY TRANSITIONS;

ARTIFICIAL INTELLIGENCE; DYNAMICAL SYSTEMS;

ARTIFICIAL EVOLUTION; DYNAMICAL SYSTEMS APPROACH; EVOLUTIONARY TRANSITIONS;

EID: 7444236062     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-540-39432-7_62     Document Type: Conference Paper

References (20)

1. Bedau, M. A., and Packard, N. H.: Measurement of evolutionary activity, teleology, and life. In: C. G. Langton, C. Taylor, J. D. Farmer, and S. Rasmussen, (eds.): Proceedings of Artificial Life II, Addison-Wesley, Redwood City, CA, (1992), 431-461
2. Bedau, M. A., Snyder, E., and Packard, N. H.: A classification of long-term evolutionary dynamics. In: C. Adami, R. Belew, H. Kitano, and C. Taylor, (eds.): Proceedings of Artificial Life VI, Los Angeles, MIT Press, Cambridge, MA, (1998), 228-237
3. Channon, A. D.: Passing the ALife test: Activity statistics classify evolution in Geb as unbounded. In: J. Kelemen, P. Sosik (eds.): Advances in Artificial Life, Proceedings of 6th European Conference (ECAL 2001), Prague, Czech Republic, Springer, (2001)
4. Pachepsky, E., Taylor, T., Jones, S.: Mutualism promotes diversity and stability in a simple artificial ecosystem. Artificial Life, Vol. 8(1). MIT Press, (2002), 5-24
5. Adami, C., Ofria, C., Collier, T. C.: Evolution of biological complexity. Proc. Nat. Acad. Sci. 97, (2000), 4463-4468
6. Adami, C.: Introduction to Artificial Life. Springer, New York, (1998)
7. Nehaniv, C. L.: Measuring evolvability as the rate of complexity increase. In: C. C. Maley and E. Boudreau, (eds.): Artificial Life VII Workshop Proceedings, (2000), 55-57
8. Nehaniv, C. L. and Rhodes, J. L., The evolution and understanding of biological complexity from an algebraic perspective. Artificial Life, 6(1). MIT Press, (2000), 45-67
9. Cliff, D., Miller, G. F.: Tracking the Red Queen: Measurements of adaptive progress in coevolutionary simulations. In: F. Moran, A. Moreno, J. J. Merelo and P. Cachon (eds): Advances in Artificial Life, Proceedings of the Third European Conference on Artificial Life (ECAL95), Lecture Notes in Artificial Intelligence 929, Springer Verlag, (1995) 200-218
10. van Nimwegen, E., Crutchfield, J. P., Mitchell, M.: Statistical Dynamics of the Royal Road Genetic Algorithm. Theoretical Computer Science, 229, (1999)
11. Nix, A. E., Vose, M. D.: Modeling genetic algorithms with Markov chains. Annals of Mathematics and Artificial Intelligence, 5, (1991)
12. Vose, M. D., Liepins, G. E.: Punctuated equilibria in genetic search. Complex Systems, 5, (1991)
13. Prugel-Bennett, A., Shapiro, J. L.: Analysis of genetic algorithms using statistical mechanics. Physical Review Letters, 72(9), (1994) 1305-1309
14. Prugel-Bennett, A., Shapiro, J. L.: The dynamics of a genetic algorithm in simple random Ising systems. Physica D, 104 (1), (1997), 75-114
15. Rattray, M., Shapiro, J. L.: The dynamics of a genetic algorithm for a simple learning problem. J. of Phys. A, 29(23), (1996), 7451-7473
16. Riziki, M.M., Conrad, M.: Computing the Theory of Evolution. Physica D, 22, (1986), 83-99
17. Packard, N.: Intrinsic adaptation in a simple model for evolution. In: C.G. Langton (ed.): Artificial life, Redwood City, Addison-Wesley, CA, (1989), 141-155
18. Ackley, D., Littman, M.: Interactions between learning and evolution. In: Langton, C. G., Taylor, C., Farmer, J. D., and Rasmussen, S. (eds.): Artificial Life II. Addison-Wesley, (1992), 487-509
19. Yaeger, L.: Computational Genetics, Physiology, Learning, Vision, and Behavior or PolyWord: Life in a New Context. In Langton, C. G. (ed.): Artificial Life III. Addison-Wesley, (1994), 263-298
20. Crutchfield, J. P.: When Evolution is Revolution-Origins of Innovation. In James P. Crutchfield, J. P. and Schuster, P. (eds.): Evolutionary Dynamics: Exploring the Interplay of Selection, Accident, Neutrality, and Function. Oxford University Press, (2002), 101-134