DFA Learning of Opponent Strategies
Gilbert L. Peterson, Diane J. Cook · 1998
This work studies the control of robots in the adversarial world of "Hunt the Wumpus". The hybrid learning algorithm which controls the robots behavior is a combination of a modified RPNI algorithm, and a utility update algorithm. The modified RPNI algorithm is a DFA learning algorithm, to learn opponents' strategies. An utility update algorithm is used to quickly derive a successful conclusion to the mission of the agent using information gleaned from the modified RPNI. 1 Introduction Developing single purpose learning algorithms for manipulating robots in a given domain, has given way to using hybrid learning algorithms that yield a more robust behavior. An approach to combine a planner with a reactive agent to play the game of soccer has been explored in the literature (Sahota 1994). In this paper, we are interested in developing a hybrid learning algorithm to manipulate robots in an adversarial game, often known as "Hunt the Wumpus". In the wumpus world, there are two a...