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» Arguing Using Opponent Models
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ESAW
2004
Springer
14 years 27 days ago
Motivation-Based Selection of Negotiation Opponents
Abstract. If we are to enable agents to handle increasingly greater levels of complexity, it is necessary to equip them with mechanisms that support greater degrees of autonomy. Th...
Stephen J. Munroe, Michael Luck
ROBOCUP
2005
Springer
91views Robotics» more  ROBOCUP 2005»
14 years 29 days ago
Gaze Direction Determination of Opponents and Teammates in Robot Soccer
Gaze direction determination of opponents and teammates is a very important ability for any soccer player, human or robot. However, this ability is still not developed in any of th...
Patricio Loncomilla, Javier Ruiz-del-Solar
ATAL
2008
Springer
13 years 9 months ago
MB-AIM-FSI: a model based framework for exploiting gradient ascent multiagent learners in strategic interactions
Future agent applications will increasingly represent human users autonomously or semi-autonomously in strategic interactions with similar entities. Hence, there is a growing need...
Doran Chakraborty, Sandip Sen
CIG
2006
IEEE
14 years 1 months ago
Evolving Adaptive Play for the Game of Spoof Using Genetic Programming
Abstract— Many games require opponent modelling for optimal performance. The implicit learning and adaptive nature of evolutionary computation techniques offer a natural way to d...
Mark Wittkamp, Luigi Barone
COLCOM
2008
IEEE
14 years 1 months ago
Learning Models of the Negotiation Partner in Spatio-temporal Collaboration
Abstract. We describe an approach for learning the model of the opponent in spatio-temporal negotiation. We use the Children in the Rectangular Forest canonical problem as an examp...
Yi Luo, Ladislau Bölöni