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...
We develop a revealed-preferencetheory for multiple agents. Some features of our construction, which draws heavily on Jeffrey's utility theory and on formal constructions by D...
In strategic multiagent decision making, it is often the case that a strategic reasoner must hold beliefs about other agents and use these beliefs to inform its decision making. T...
Abstract. Constraint solving problems (CSPs) represent a formalization of an important class of problems in computer science. We propose here a solving methodology based on the nam...
This paper presents CBRetaliate, an agent that combines Case-Based Reasoning (CBR) and Reinforcement Learning (RL) algorithms. Unlike most previous work where RL is used to improve...
Bryan Auslander, Stephen Lee-Urban, Chad Hogg, H&e...