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Toward a gene regulatory network model for evolving chemotaxis behavior

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4 Author(s)
Samways, N. ; Sch. of Comput. Sci., Birmingham Univ., Birmingham ; Yaochu Jin ; Xin Yao ; Sendhoff, B.

Inspired from bacteria, a gene regulatory network model for signal transduction is presented in this paper. After describing experiments on stabilizing the population size for sustained open-ended evolution, we examine the ability of the model to evolve gradient-following behavior resembling bacterial chemotaxis. Under the conditions defined in this paper, an overwhelming chemotaxis behavior does not seem to emerge. Further experimentation suggests that chemotaxis is selectively favored, however, it is shown that the gradient information, which is critical for evolving chemotaxis, is heavily degraded under the current regime. It is hypothesized that lack of consistent gradient information results in the selection of non chemotaxis behavior. Future work on revising the model as well as the environmental setups is discussed.

Published in:

Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on

Date of Conference:

1-6 June 2008