Evolving hybrid time-shuffled behavior of agents

We searched for methods to evolve the hybrid behavior of moving agents for the All-to-All Communication task. The multi-agent system is modeled in two-dimensional Cellular Automata. An agent is controlled by one or more finite state machines. We use a time-shuffling method to join the state machines into one hybrid ¿algorithm¿. We propose a method to directly evolve a hybrid behavior consisting of multiple state machines including their time-shuffling periods. We compared the evolved hybrid algorithms to other evolved non-hybrid algorithms (consisting of only one finite state machine) and to hybrid algorithms that were composed of separately evolved non-hybrid algorithms. The performance of the directly evolved hybrid algorithms was significantly better, and the computation time for the evolution was roughly the same.