Recently researchers have introduced methods to develop reusable knowledge in reinforcement learning (RL). In this paper, we define simple principles to combine skills in reinforce...
The existing reinforcement learning methods have been seriously suffering from the curse of dimension problem especially when they are applied to multiagent dynamic environments. ...
Abstract. We study optimal control in large stochastic multi-agent systems in continuous space and time. We consider multi-agent systems where agents have independent dynamics with...
A Skilligent robot must be able to learn skills autonomously to accomplish a task. "Skilligence" is the capacity of the robot to control behaviors reasonably, based on th...
In addressing the challenge of exponential scaling with the number of agents we adopt a cluster-based representation to approximately solve asymmetric games of very many players. ...