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ATAL
2009
Springer
15 years 4 months ago
Stronger CDA strategies through empirical game-theoretic analysis and reinforcement learning
We present a general methodology to automate the search for equilibrium strategies in games derived from computational experimentation. Our approach interleaves empirical game-the...
L. Julian Schvartzman, Michael P. Wellman
ROBOCUP
2001
Springer
96views Robotics» more  ROBOCUP 2001»
15 years 2 months ago
Strategy Learning for a Team in Adversary Environments
Team strategy acquisition is one of the most important issues of multiagent systems, especially in an adversary environment. RoboCup has been providing such an environment for AI a...
Yasutake Takahashi, Takashi Tamura, Minoru Asada
IJCAI
2007
14 years 11 months ago
Analogical Learning in a Turn-Based Strategy Game
A key problem in playing strategy games is learning how to allocate resources effectively. This can be a difficult task for machine learning when the connections between actions a...
Thomas R. Hinrichs, Kenneth D. Forbus
ICRA
2010
IEEE
128views Robotics» more  ICRA 2010»
14 years 8 months ago
A game-theoretic procedure for learning hierarchically structured strategies
— This paper addresses the problem of acquiring a hierarchically structured robotic skill in a nonstationary environment. This is achieved through a combination of learning primi...
Benjamin Rosman, Subramanian Ramamoorthy
SAGT
2009
Springer
192views Game Theory» more  SAGT 2009»
15 years 4 months ago
Learning and Approximating the Optimal Strategy to Commit To
Computing optimal Stackelberg strategies in general two-player Bayesian games (not to be confused with Stackelberg strategies in routing games) is a topic that has recently been ga...
Joshua Letchford, Vincent Conitzer, Kamesh Munagal...