In this paper, we describe a cooperative transportation problem with two humanoid robots and introduce a machine learning approach to solving the problem. The difficulty of the ta...
We introduce new, efficient algorithms for value iteration with multiple reward functions and continuous state. We also give an algorithm for finding the set of all nondominated a...
Daniel J. Lizotte, Michael H. Bowling, Susan A. Mu...
Multiagent reinforcement learning problems are especially difficult because of their dynamism and the size of joint state space. In this paper a new benchmark problem is proposed, ...
We study how to learn to play a Pareto-optimal strict Nash equilibrium when there exist multiple equilibria and agents may have different preferences among the equilibria. We focu...
This paper introduces an approach to automatic basis function construction for Hierarchical Reinforcement Learning (HRL) tasks. We describe some considerations that arise when con...