Exploiting regularity without development

AAAI Fall Symposium - Technical Report

Volumn FS-06-03, Issue , 2006, Pages 49-56

  Stanley, Kenneth O ^a  

^a University of Central Florida   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTATIONAL COMPLEXITY; GENETIC ALGORITHMS; NEURAL NETWORKS; VIRTUAL REALITY;

COMPOSITIONAL PATTERN PRODUCING NETWORKS (CPPNS); COMPUTATIONAL ABSTRACTIONS; NATURAL DEVELOPMENT; NATURAL ORGANISMS;

NATURAL SCIENCES COMPUTING;

EID: 33947227425     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (38)

1. Altenberg, L. 1994. Evolving better representations through selective genome growth. In Proc. of the IEEE World Congress on Comp. Intelligence, 182-187. Piscataway, NJ: IEEE Press.
2. Andersen, T.; Otter, C.; Petschulat, C.; Eoff, U.; Menten, T.; Davis, R.; and Crowley, B. 2005. A biologically-derived approach to tissue modeling. In et al, J. W., ed., Technology and Informatics. Amsterdam: IOS Press. 15-21.
3. Angeline, P. J.; Saunders, G. M; and Pollack, J. B. 1993. An evolutionary algorithm that constructs recurrent neural networks. IEEE Transactions on Neural Networks 5:54-65.
4. Astor, J., and Adami, C. 2000. A developmental model for the evolution of artificial neural networks. Artificial Life 6(3): 189-218.
5. Bentley, P. J., and Kumar, S. 1999. The ways to grow designs: A comparison of embryogenies for an evolutionary design problem. In Proc. of the Genetic and Evolutionary Computation Conf. (GECCO-1999), 35-43. San Francisco: Kaufmann.
6. Bongard, J. C. 2002. Evolving modular genetic regulatory networks. In Proc. of the 2002 Congress on Evolutionary Comp..
7. Curtis, D.; Apfeld, J.; and Lehmann, R. 1995. Nanos is an evolutionarily conserved organizer of anterior-posterior polarity. Development 121:1899-1910.
8. Dawkins, R. 1986. The Blind Watchmaker. Essex, U.K.: Longman.
9. De Jong, E. D., and Thierens, D. 2004. Exploiting modularity, hierarchy, and repetition in variable-length problems. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2004), 1030-1040. Berlin: Springer Verlag.
10. Dellaert, F., and Beer, R. 1996. A developmental model for the evolution of complete autonomous agents. In Maes, P.; Mataric, M. J.; Meyer, J.-A.; Pollack, J.; and Wilson, S. W., eds., From Animals to Animals 4: Proc. of the Fourth International Conf. on Simulation of Adaptive Behavior. Cambridge, MA: MIT Press.
11. Federici, D. 2004. Evolving a neurocontroller through a process of embryogeny. In Schaal, S.; Ijspeert, A. J.; Billard, A.; Vijayakumar, S.; Hallam, J.; and Jean-Arcady., eds., Proc. of the Eighth International Conf. on Simulation and Adaptive Behavior (SAB-2004), 373-384. Cambridge, MA: MIT Press.
12. Gomez, F., and Miikkulainen, R. 1999. Solving non-Markovian control tasks with neuroevolution. In Proc. of the 16th Int. Joint Conf. on Artif. Int., 1356-1361. San Francisco: Kaufmann.
13. Gruau, F.; Whitley, D.; and Pyeatt, L. 1996. A comparison between cellular encoding and direct encoding for genetic neural networks. In Koza, J. R.; Goldberg, D. E.; Fogel, D. B.; and Riolo, R. L., eds., Genetic Programming 1996: Proceedings of the First Annual Conference, 81-89. Cambridge, MA: MIT Press.
14. Hornby, G. S., and Pollack, J. B. 2002. Creating high-level components with a generative representation for body-brain evolution. Artificial Life 8(3).
15. Komosinski, M., and Rotaru-Varga, A. 2001. Comparison of different genotype encodings for simulated 3D agents. Artificial Life 7(4):395-418.
16. Koza, J. R. 1992. Genetic Programming: On the Programming of Computers by Means of Natural Selection. Cambridge, MA: MIT Press.
17. Lall, S., and Patel, N. 2001. Conservation and divergence in molecular mechanisms of axis formation. Annual Review of Genetics 35:407-447.
18. Lindenmayer, A. 1968. Mathematical models for cellular interaction in development parts I and II. Journal of Theoretical Biology 18:280-299 and 300-315.
19. Martin, A. P. 1999. Increasing genomic complexity by gene duplication and the origin of vertebrates. The American Naturalist 154(2):111-128.
20. Meinhardt, H. 1982. Models of Biological Pattern Formation. London: Academic Press.
21. Miller, J. F., and Thomson, P. 2000. Cartesian genetic programming. In Proc. of the 3rd European Conf. on Genetic Programming publ. as Lect. Notes in Comp. Sci., Vol. 1802, 121-132.
22. Miller, J. F. 2004. Evolving a self-repairing, self-regulating, French flag organism. In Proc. of the Genetic and Evolutionary Computation Conf. (GECCO-2004). Berlin: Springer Verlag.
23. Radcliffe, N. J. 1993. Genetic set recombination and its application to neural network topology optimization. Neural computing and applications 1(1):67-90.
24. Raff, R. A. 1996. The Shape of Life: Genes, Development, and the Evolution of Animal Form. Chicago: The U. of Chicago Press.
25. Roggen, D., and Federici, D. 2004. Multi-cellular development: Is there scalability and robustness to gain. In Proceedings of the 8th International Conference on Parallel Problem Solving from Nature (PPSN VIII), 391-400.
26. Saravanan, N., and Fogel, D. B. 1995. Evolving neural control systems. IEEE Expert 23-27.
27. Sims, K. 1991. Artificial evolution for computer graphics. In Proceedings of the 18th annual conference on Computer graphics and interactive techniques (SIGGRAPH '91), 319-328. New York, NY: ACM Press.
28. Sims, K. 1994. Evolving 3D morphology and behavior by competition. In Brooks, R. A., and Maes, P., eds., Fourth International Workshop on the Synthesis and Simulation of Living Systems (Artificial Life IV). Cambridge, MA: MIT Press. 28-39.
29. Stanley, K. O., and Miikkulainen, R. 2002. Evolving neural networks through augmenting topologies. Evolutionary Computation 10:99-127.
30. Stanley, K. O., and Miikkulainen, R. 2003. A taxonomy for artificial embryogeny. Artificial Life 9(2):93-130.
31. Stanley, K. O., and Miikkulainen, R. 2004. Competitive coevolution through evolutionary complexification. Journal of Artificial Intelligence Research 21:63-100.
32. Stanley, K. O. 2006. Comparing artificial phenotypes with natural biological patterns. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) Workshop Program. New York, NY: ACM Press.
33. Takagi, H. 2001. Interactive evolutionary computation: Fusion of the capacities of EC optimization and human evaluation. Proceedings of the IEEE 89(9): 1275-1296.
34. True, J., and Carroll, S. 2002. Gene co-option in physiological and morphological evolution. Annual Review of Cell and Developmtnal Biology 18:53-80.
35. Turing, A. 1952. The chemical basis of morphogenesis. Philosophical Transactions of the Royal Society B 237:37-72.
36. Watson, J. D.; Hopkins, N. H.; Roberts, J. W.; Steitz, J. A.; and Weiner, A. M. 1987. Molecular Biology of the Gene. Menlo Park, CA: The Benjamin Cummings Publishing Company, Inc., fourth edition.
37. Yao, X. 1999. Evolving artificial neural networks. Proceedings of the IEEE 87(9):1423-1447.
38. Zigmond, M. J.; Bloom, F. E.; Landis, S. C.; Roberts, J. L.; and Squire, L. R., eds. 1999. Fundamental Neuroscience. London: Academic Press.