"Niche selection" and the evolution of complex behavior in a changing environment - A simulation

Artificial Life

Volumn 5, Issue 3, 1999, Pages 271-289

  Walker, Richard ^a  

^a UNIVERSITY OF PALERMO   (Italy)

Author keywords

Evolution; Learning; Neural networks; Niche selection

Indexed keywords

ANIMAL; ARTICLE; ARTIFICIAL NEURAL NETWORK; ENVIRONMENT; EVOLUTION; GENETIC SELECTION; HUMAN; LEARNING;

ANIMALS; ENVIRONMENT; EVOLUTION; HUMANS; LEARNING; NEURAL NETWORKS (COMPUTER); SELECTION (GENETICS);

EID: 0033138916     PISSN: 10645462     EISSN: None     Source Type: Journal    
DOI: 10.1162/106454699568782     Document Type: Article

References (22)

1. Bak, P. (1996). How Nature Works. New York, NY: Springer-Verlag.
2. Belew, R. K., & Mitchell, M. (1996). Introduction. In R. K. Belew & M. Mitchell (Eds.), Adaptive Individuals in Evolving Populations. Reading, MA: Addison-Wesley.
3. Chaitin, G. J. (1975). Randomness and mathematical proof. Scientific American, 232, 47-52.
4. Clark, A. (1997). Being There, Putting Brain, Body and World Together. Cambridge, MA: MIT Press.
5. Crick, F. (1989). The recent excitement about neural networks. Nature, 337, 129-132.
6. Dreyfuss, H. L. (1972). What Computers Can't Do, A Critique of Artificial Reason. New York, NY: Harper and Row.
7. Eigen, M., & Schuster, P. (1978). The hypercycle part B: "The abstract hypercycle." Naturwissenschaften, 65, 7-41.
8. Garey, M. R., & Johnson, D. S. (1979). Computers and Intractability - a Guide to the Theory of NP-Completeness. New York, NY: W. H. Freeman and Company.
9. Gould, S. J. (1991). Exaptation: A crucial tool for an evolutionary psychology. J. Soc. Issues, 3, 43-65.
10. Gould, S. J. (1996). Full House. New York, NY: Three Rivers Press.
11. Holland, J. H. (1975). Adaptation in Natural and Artificial Systems. Ann Arbor, MI: University of Michigan Press.
12. Judd, J. S. (1990). Neural Network Design and the Complexity of Learning. Cambridge, MA: MIT Press.
13. Kauffman, S. A., & Johnson, S. (1992). Co-Evolution to the edge of chaos: Coupled fitness landscapes, poised states and co-evolutionary avalanches. Artificial Life II, 325-369, Redwood City, CA: Addison-Wesley.
14. Kauffman, S. A. (1993). The Origins of Order. New York, NY: Oxford University Press.
15. Langton, R. A. (1989). (Ed.). Artificial Life I. Redwood City, CA: Addison-Wesley.
16. Littman, M. (1996). Simulations combining evolution and learning. In R. K. Belew & M. Mitchell (Eds.), Adaptive Individuals in Evolving Populations (pp. 465-477). Reading, MA: Addison-Wesley.
17. Lund, H. H., & Parisi, D. (1996). Pre-adaptations in populations of neural networks, evolving in a changing environment. Artificial Life, 2, 179-197.
18. Minsky, M., & Pappert, S. (1969). Perceptrons. Cambridge, MA: MIT Press.
19. Rosenblatt, F. (1958). The perceptron: A probabilistic model for information storage and organization in the brain. Psychological Review, 65, 386-408.
20. Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986). Learning internal representations by error propagation. In D. E. Rumelhart, J. L. McClelland, & PDP Research Group I (Eds.), Parallel Distributed Processing (pp. 318-364). Cambridge, MA: MIT Press.
21. Waddington, C. H. (1975). Evolution of an Evolutionist. Ithaca, NY: Cornell University Press.
22. Wright, S. (1931). Evolution in mendelian populations. Genetics, 16, 97.