Genetic Programming and Co-Evolution with Exogenous Fitness in an Artificial Life Environment (1999) [1 citations — 0 self]
http://www.cs.jhu.edu/~jsquad/pubs/cec-1999.pdf
http://www.cs.jhu.edu/~sheppard/cec99.ps.gz
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author = {Michael Waters and John Sheppard},
title = {Genetic Programming and Co-Evolution with Exogenous Fitness in an Artificial Life Environment},
booktitle = {Proceedings of the Congress on Evolutionary Computation},
year = {1999},
pages = {pages},
publisher = {IEEE Press}
}
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Abstract:
The study of artificial life involves simulating biological or sociological processes with a computer. Combining artificial life with techniques from evolutionary computation frequently involves modeling the behavior or decision processes of artificial organisms within a society in such a way that genetic algorithms can be applied to modify these models and enhance behavior over time. Typically, endogenous fitness is used with co-evolution. In this paper, we explore the use of an exogenous fitness function with genetic programming and co-evolution to develop individuals and species capable of competing in a hostile environment. To facilitate the study, we use a commercially available environment¾AI Wars¾to host the organisms and run the experiments. Results from our experiments, though preliminary, indicate the ability of co-evolution, genetic programming, and exogenous fitness to evolve fit individuals. The results also suggest the ability to assess the nature of the fitness landscape...
