Passing the alife test: Activity statistics classify evolution in geb as unbounded

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

Volumn 2159, Issue , 2001, Pages 417-426

  Channon, Alastair ^a  

^a UNIVERSITY OF PORTSMOUTH   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER SCIENCE; COMPUTERS;

ARTIFICIAL SYSTEMS; COURSE OF ACTION; EVOLUTIONARY DYNAMICS;

ARTIFICIAL LIFE;

EID: 84949750379     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-44811-x_45     Document Type: Conference Paper

References (10)

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2. Bedau, M. A., Snyder, E., and Packard, N. H. A classification of longterm evolutionary dynamics. In Proceedings of Artificial Life VI, Los Angeles (Cambridge, MA, 1998), C. Adami, R. Belew, H. Kitano, and C. Taylor, Eds., MIT Press, pp. 228–237.
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8. Nehaniv, C. L. Evolvability in biologically-inspired robotics: Solutions for achieving open-ended evolution. In Sensor Fusion and Decentralized Control in Robotic Systems III, SPIE Proceedings 4196 (2000), P. McKee, G. T. Schenker, Ed., pp. 13–26.
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10. Rechtsteiner, A., and Bedau, M. A. A generic neutral model for measuring excess evolutionary activity of genotypes. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO99) (San Francisco, CA, 1999), W. Banzhaf, J. Daida, A. E. Eiben, M. H. Garzon, V. Honavar, M. Jakiela, and R. E. Smith, Eds., Morgan Kaufmann, pp. 1366–1373. Volume 2.