Rectangular vs triangular routing with evolved agents

A multiple target searching with evolved agents is per formed in a cellular automata network to solve the routing problem in the square toroidal grid. The agents shall behave according to a control algorithm implemented as finite state machine (FSM). Using a genetic procedure, algorithms are evolved that could solve successfully all the training cases under consideration. In order to avoid dead locks, a certain amount of randomness is added to the FSM. Intelligent random walkers (IW) are also considered. This paper is a companion paper on a previous work dealing with a similar protocol running in the triangular torus. It yields comparative performance results between rectangular and triangular routing, giving advantage to the latter.