@inproceedings{24c1c1a360f24254933b899cd3b0aab6,
title = "A near optimal policy for channel allocation in cognitive radio",
abstract = "Several tasks of interest in digital communications can be cast into the framework of planning in Partially Observable Markov Decision Processes (POMDP). In this contribution, we consider a previously proposed model for a channel allocation task and develop an approach to compute a near optimal policy. The proposed method is based on approximate (point based) value iteration in a continuous state Markov Decision Process (MDP) which uses a specific internal state as well as an original discretization scheme for the internal points. The obtained results provide interesting insights into the behavior of the optimal policy in the channel allocation model.",
author = "Sarah Filippi and Olivier Capp{\'e} and Fabrice Cl{\'e}rot and Eric Moulines",
year = "2008",
month = dec,
day = "1",
doi = "10.1007/978-3-540-89722-4\_6",
language = "English",
isbn = "3540897216",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "69--81",
booktitle = "Recent Advances in Reinforcement Learning - 8th European Workshop, EWRL 2008, Revised and Selected Papers",
note = "8th European Workshop on Reinforcement Learning, EWRL 2008 ; Conference date: 30-06-2008 Through 03-07-2008",
}