Efficient Learning Equilibrium (ELE) is a natural solution concept for multi-agent encounters with incomplete information. It requires the learning algorithms themselves to be in ...
An interesting problem which has been widely investigated is under what circumstances will a society of rational agents realize some particular stable situations, and whether they ...
In many Multi-Agent Systems (MAS), agents (even if selfinterested) need to cooperate in order to maximize their own utilities. Most of the multi-agent learning algorithms focus on...
Jose Enrique Munoz de Cote, Alessandro Lazaric, Ma...
Learning to converge to an efficient, i.e., Pareto-optimal Nash equilibrium of the repeated game is an open problem in multiagent learning. Our goal is to facilitate the learning ...
Learning in many multi-agent settings is inherently repeated play. This calls into question the naive application of single play Nash equilibria in multi-agent learning and sugges...