Many internet and enterprise applications now not only use XML (eXtensible Markup Language) as a medium for communication but also for storing their data either temporarily for an...
Hierarchical reinforcement learning (RL) is a general framework which studies how to exploit the structure of actions and tasks to accelerate policy learning in large domains. Pri...
Abstract--Proper admission control in cognitive radio networks is critical in providing QoS guarantees to secondary unlicensed users. In this paper, we study the admission control ...
Several formalisms exist to express and solve decision problems. Each is designed to capture different kinds of knowledge: utilities expressing preferences, uncertainties on the en...
Partially Observable Markov Decision Processes (POMDPs) have succeeded in planning domains that require balancing actions that increase an agent's knowledge and actions that ...