Reward shaping is a well-known technique applied to help reinforcement-learning agents converge more quickly to nearoptimal behavior. In this paper, we introduce social reward sha...
Monica Babes, Enrique Munoz de Cote, Michael L. Li...
We describe a generalized Q-learning type algorithm for reinforcement learning in competitive multi-agent games. We make the observation that in a competitive setting with adaptive...
Pieter Jan't Hoen, Sander M. Bohte, Han La Poutr&e...
We utilize evolutionary game theory to study the evolution of cooperative societies and the behaviors of individual agents (i.e., players) in such societies. We present a novel pla...
Kan-Leung Cheng, Inon Zuckerman, Ugur Kuter, Dana ...