Multiple-agent probabilistic pursuit-evasion games

We develop a probabilistic framework for pursuit-evasion games. We propose a "greedy" policy to control a swarm of autonomous agents in the pursuit of one or several evaders. At each instant of time this policy directs the pursuers to the locations that maximize the probability of finding an evader at that particular time instant. It is shown that, under mild assumptions, this policy guarantees that an evader is found in finite time and that the expected time needed to find the evader is also finite. Simulations are included to illustrate the results.