Tactical modularity for evolutionary animats

In this paper, we use a massive modular architecture for the generation of complex behaviours in complex robots within the evolutionary robotics framework. We define two different ways of introducing modularity in neural controllers using evolutionary techniques, which we call strategic and tactical modularity, and show at what modular levels each one acts and how can they be combined for the generation of a completely modular controller for a neural networks based animat. Implementation results are presented for the garbage collector problem using a khepera robot and compared with previous results from other researchers.