The question investigated in this paper is to what extent an input representation influences the success of learning, in particular from the point of view of analyzing agents that...
One of the key problems in reinforcement learning is balancing exploration and exploitation. Another is learning and acting in large or even continuous Markov decision processes (...
Lihong Li, Michael L. Littman, Christopher R. Mans...
Decentralized partially observable MDPs (DEC-POMDPs) provide a rich framework for modeling decision making by a team of agents. Despite rapid progress in this area, the limited sc...
Abstract. In this paper, we identify some problems with current formalizations of conditional commitments, i.e. commitments to achieve a goal if some condition becomes true. We pre...
In open settings, the participants are autonomous and there is no central authority to ensure the felicity of their interactions. When agents interact in such settings, each relie...