Thresholded Rewards: Acting Optimally in Timed, Zero-Sum Games

In timed, zero-sum games, the goal is to maximize the probability of winning, which is not necessarily the same as maximizing our expected reward. We consider cumulative intermediate reward to be the difference between our score and our opponent’s score; the “true” reward of a win, loss, or tie is determined at the end of a game by applying a threshold function to the cumulative intermediate reward. We introduce thresholded-rewards problems to capture this dependency of the final reward outcome on the cumulative intermediate reward. Thresholded-rewards problems reflect different real-world stochastic planning domains, especially zero-sum games, in which time and score need to be considered. We investigate the application of thresholded rewards to finitehorizon Markov Decision Processes (MDPs). In general, the optimal policy for a thresholded-rewards MDP will be nonstationary, depending on the number of time steps remaining and the cumulative intermediate reward. We introduce ...

• Type: Conference
• Year: 2007
• Where: AAAI
• Authors: Colin McMillen, Manuela M. Veloso
• Keywords: AAAI 2007, Cumulative Intermediate Reward, Intelligent Agents, Zero-sum Games, final Reward Outcome