Bayesian Reinforcement Learning has generated substantial interest recently, as it provides an elegant solution to the exploration-exploitation trade-off in reinforcement learning...
Markov Decision Processes (MDP) have been widely used as a framework for planning under uncertainty. They allow to compute optimal sequences of actions in order to achieve a given...
When arriving to Hong Kong from China, the first difficulty of the new arrival women of the grassroots class is usually environmental stress. Their socio-economic situations often...
We study an approach for performing concurrent activities in Markov decision processes (MDPs) based on the coarticulation framework. We assume that the agent has multiple degrees ...
For a system of cooperative mobile robots to be effective in real-world applications, it must be able to efficiently execute a wide class of complex tasks in potentially unknown a...