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

Comments

This article was originally published as: 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. Original article available here

© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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

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