In this paper we consider approximate policy-iteration-based reinforcement learning algorithms. In order to implement a flexible function approximation scheme we propose the use o...
Amir Massoud Farahmand, Mohammad Ghavamzadeh, Csab...
Query optimization in data integration requires source coverage and overlap statistics. Gathering and storing the required statistics presents many challenges, not the least of wh...
Abstract--In this paper, d-AdaptOR, a distributed opportunistic routing scheme for multi-hop wireless ad-hoc networks is proposed. The proposed scheme utilizes a reinforcement lear...
Abhijeet Bhorkar, Mohammad Naghshvar, Tara Javidi,...
Abstract--This study proposes an efficient self-evolving evolutionary learning algorithm (SEELA) for neurofuzzy inference systems (NFISs). The major feature of the proposed SEELA i...
PAC-MDP algorithms approach the exploration-exploitation problem of reinforcement learning agents in an effective way which guarantees that with high probability, the algorithm pe...