Formalizing the Ant Algorithms in terms of Reinforcement Learning

. In this paper we place ant algorithms in a reinforcement learning framework. We concentrate on the original Ant System and we briey discuss Ant Colony system. We show that ant-quantity and ant-density can be considered as TD(0) algorithms which only take into account immediate reinforcement. Whereas ant cycle is basically an onpolicy Monte Carlo method. We introduce the notion of decay traces, for modeling the decay of trail.