Our goal is to provide learning mechanisms to game agents so they are capable of adapting to new behaviors based on the actions of other agents. We introduce a new on-line reinfor...
Games are used to evaluate and advance Multiagent and Artificial Intelligence techniques. Most of these games are deterministic with perfect information (e.g. Chess and Checkers)....
This paper introduces a multiagent reinforcement learning algorithm that converges with a given accuracy to stationary Nash equilibria in general-sum discounted stochastic games. ...
Abstract— The usage of memory in coevolutionary systems offers a wide range of research possibilities, especially when evolving computationally intelligent computer players for g...
The Prisoner's Dilemma and the Public Goods Game are models to study mechanisms leading to the evolution of cooperation. From a simplified rational and egoistic perspective t...