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ROBOCUP
2004
Springer
106views Robotics» more  ROBOCUP 2004»
13 years 9 months ago
Predicting Opponent Actions by Observation
In competitive domains, the knowledge about the opponent can give players a clear advantage. This idea lead us in the past to propose an approach to acquire models of opponents, ba...
Agapito Ledezma, Ricardo Aler, Araceli Sanch&iacut...
IDEAL
2009
Springer
13 years 8 months 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...
ATAL
2011
Springer
12 years 4 months ago
Game theory-based opponent modeling in large imperfect-information games
We develop an algorithm for opponent modeling in large extensive-form games of imperfect information. It works by observing the opponent’s action frequencies and building an opp...
Sam Ganzfried, Tuomas Sandholm
AAAI
2000
13 years 5 months ago
Defining and Using Ideal Teammate and Opponent Agent Models
A common challenge for agents in multiagent systems is trying to predict what other agents are going to do in the future. Such knowledge can help an agent determine which of its c...
Peter Stone, Patrick Riley, Manuela M. Veloso
ESWA
2008
169views more  ESWA 2008»
13 years 3 months ago
Predicting opponent's moves in electronic negotiations using neural networks
Electronic negotiation experiments provide a rich source of information about relationships between the negotiators, their individual actions, and the negotiation dynami...
Réal Carbonneau, Gregory E. Kersten, Rustam...