Toward a gene regulatory network model for evolving chemotaxis behavior

— 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 nonchemotaxis behavior. Future work on revising the model as well as the environmental setups is discussed.

• Type: Conference
• Year: 2008
• Where: CEC
• Authors: Neale Samways, Yaochu Jin, Xin Yao, Bernhard Sendhoff
• Keywords: Artificial Intelligence, Bacterial Chemotaxis, CEC 2008, Chemotaxis, Overwhelming Chemotaxis Behavior