DocumentCode
2820007
Title
Using Monte Carlo Tree Search for replanning in a multistage simultaneous game
Author
Beard, Daniel ; Hingston, Philip ; Masek, Martin
Author_Institution
Sch. of Comput. & Security Sci., Edith Cowan Univ., Perth, WA, Australia
fYear
2012
fDate
10-15 June 2012
Firstpage
1
Lastpage
8
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.
Keywords
Monte Carlo methods; game theory; tree searching; MC-TSAR; Monte Carlo tree search algorithm; Nash equilibrium strategy; battle planning scenario; multistage simultaneous game replanning; strategy selection; switching strategies; Approximation algorithms; Approximation methods; Games; Monte Carlo methods; Nash equilibrium; Planning; Security;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation (CEC), 2012 IEEE Congress on
Conference_Location
Brisbane, QLD
Print_ISBN
978-1-4673-1510-4
Electronic_ISBN
978-1-4673-1508-1
Type
conf
DOI
10.1109/CEC.2012.6256428
Filename
6256428
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