Experiments on Alternatives to Minimax Dana Nau * University of Maryland Paul Purdom Indiana University Chun-Hung Tzeng Ball State University April 23, 1993 Abstract In the field of Artificial Intelligence, traditional approaches to choosing moves in games involve the use of the minimax algorithm. However, recent research results indicate that minimaxing may not always be the best approach. In this paper we report some measurements on several model games with several different evaluation functions. These measurements show that there are some new algorithms that can make significantly better use of evaluation function values than the minimax algorithm does. Key Words : artificial intelligence, decision analysis, game trees, minimax, search. * This work was supported in part by a Presidential Young Investigator Award to Dana Nau, includ- ing matching funds from IBM Research, General Motors Research Laboratories, and Martin Marietta Laboratories. 1