Extending Korf's ideas on the pursuit problem

The prey-predator pursuit problem is referenced many times in literature. It is a generic multi-agent problem whose solutions could by applied to many particular instances. Solutions proposed usually apply non-supervised learning algorithms to train prey and predators. Most of these solutions criticize the greedy algorithm originally proposed by Korf. However, we believe that the improvement obtained by these new proposals does not pay off with relation to their complexity. The method used by Korf is a natural way to surround a prey without explicit communication between predators. The knowledge one predator has about others is limited just to what it can see. In Korf’s model, agents are able to see the complete world at once. In this paper we propose to start from Korf’s ideas and extend them to improve his model. First, we propose a simple extension of Korf’s fitness function and we consider the problems related to a partial view of the world. Second, we propose a communication protocol to partially overcome them. The final results suggest that more work needs to be done, and we propose a way to follow-on