A simple tree search method for playing Ms. Pac-Man

Abstract

Ms. Pac-Man is a challenging game for software agents that has been the focus of a significant amount of research. This paper describes the current state of a tree-search software agent that will be entered into the IEEE CIG 2009 screen-capture based Ms. Pac-Man software agent competition. While game-tree search is a staple technique for many games, this paper is, perhaps surprisingly, the first attempt we know of to apply it to Ms. Pac-Man. The approach we take is to expand a route-tree based on possible moves that the Ms. Pac-Man agent can take to depth 40, and evaluate which path is best using hand-coded heuristics. On a simulator of the game our agent has achieved a high score of 40,000, but only around 15,000 on the original game using a screen-capture interface. Our next steps are focussed on using an improved screen-capture system, and on using evolutionary algorithms to tune the parameters of the agent.