We present a general methodology to automate the search for equilibrium strategies in games derived from computational experimentation. Our approach interleaves empirical game-the...
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...
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...
— 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...
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...