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» Opponent Modeling in Poker
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ATAL
2011
Springer
12 years 7 months ago
Using iterated reasoning to predict opponent strategies
The field of multiagent decision making is extending its tools from classical game theory by embracing reinforcement learning, statistical analysis, and opponent modeling. For ex...
Michael Wunder, Michael Kaisers, John Robert Yaros...
ESAW
2004
Springer
14 years 1 months 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 1 months 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 10 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
JVCIR
2008
110views more  JVCIR 2008»
13 years 7 months ago
Video quality and system resources: Scheduling two opponents
In this article we present three key ideas which together form a flexible framework for maximizing user-perceived quality under given resources with modern video codecs (H.264). F...
Michael Roitzsch, Martin Pohlack