Document Type
Conference Proceeding
Publisher
IEEE
Faculty
Faculty of Computing, Health and Science
School
School of Computer and Security Science / Artificial Intelligence and Optimisation Research Group
RAS ID
14786
Abstract
In this study, we introduce MC-TSAR, a Monte Carlo Tree Search algorithm for strategy selection in simultaneous multistage games. We evaluate the algorithm using a battle planning scenario in which replanning is possible. We show that the algorithm can be used to select a strategy that approximates a Nash equilibrium strategy, taking into account the possibility of switching strategies part way through the execution of the scenario in the light of new information on the progress of the battle.
DOI
10.1109/CEC.2012.6256428
Access Rights
free_to_read
Comments
This is an Author's Accepted Manuscript of: Beard, D. R., Hingston, P. F., & Masek, M. (2012). Using Monte Carlo Tree Search for Replanning in a Multistage Simultaneous Game. Proceedings of 2012 IEEE Congress on Evolutionary Computation. (pp. 1-8). Brisbane, Australia. IEEE. Available here
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