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IDEAL
2009
Springer
14 years 13 days ago
The Winning Advantage: Using Opponent Models in Robot Soccer
Opponent modeling is a skill in multi-agent systems (MAS) which attempts to create a model of the behavior of the opponent. This model can be used to predict the future actions of ...
José Antonio Iglesias, Juan Antonio Fern&aa...
ICMAS
1998
13 years 9 months ago
How to Explore your Opponent's Strategy (almost) Optimally
This work presents a lookahead-based exploration strategy for a model-based learning agent that enables exploration of the opponent's behavior during interaction in a multi-a...
David Carmel, Shaul Markovitch
ACG
2003
Springer
14 years 1 months ago
Opponent-Model Search in Bao: Conditions for a Successful Application
Abstract Opponent-Model search is a game-tree search method that explicitly uses knowledge of the opponent. There is some risk involved in using Opponent-Model search. Both the pre...
H. H. L. M. Donkers, H. Jaap van den Herik, Jos W....
AAAI
2008
13 years 10 months ago
Bayes-Relational Learning of Opponent Models from Incomplete Information in No-Limit Poker
We propose an opponent modeling approach for no-limit Texas hold-em poker that starts from a (learned) prior, i.e., general expectations about opponent behavior and learns a relat...
Marc J. V. Ponsen, Jan Ramon, Tom Croonenborghs, K...
AAAI
2006
13 years 9 months ago
Know Thine Enemy: A Champion RoboCup Coach Agent
In a team-based multiagent system, the ability to construct a model of an opponent team's joint behavior can be useful for determining an agent's expected distribution o...
Gregory Kuhlmann, William B. Knox, Peter Stone