Abstract--This article deals with the issue of concept learning and tries to have a game theoretic view over the process of cooperative concept learning among agents in a multi-age...
Multiagent systems are rapidly finding applications in a variety of domains, including robotics, distributed control, telecommunications, and economics. The complexity of many task...
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, ...
As applications for artificially intelligent agents increase in complexity we can no longer rely on clever heuristics and hand-tuned behaviors to develop their programming. Even t...
Shawn Arseneau, Wei Sun, Changpeng Zhao, Jeremy R....
The existing reinforcement learning methods have been seriously suffering from the curse of dimension problem especially when they are applied to multiagent dynamic environments. ...