Evolutionary discovery of arbitrary self-replicating structures

Authors:
Zhijian Pan;James Reggia
Affiliations:
Computer Science Dept. & UMIACS, University of Maryland, College Park, MD;Computer Science Dept. & UMIACS, University of Maryland, College Park, MD
Venue:
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part II
Year:
2005

Citing 6
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Abstract

In this paper we describe our recent use of genetic programming methods to automatically discover CA rule sets that produce self-replication of arbitrary given structures. Our initial results have produced larger, more rapidly replicating structures than past evolutionary models while requiring only a small fraction of the computational time needed in past similar studies. We conclude that genetic programming provides a very powerful tool for discovering novel CA models of self-replicating systems and possibly other complex systems.