Institutional Repository
Technical University of Crete
Technical University of Crete
EN
|
EL
| URI | http://purl.tuc.gr/dl/dias/157117EC-5401-47A1-B453-9D39AAFFC2E2 | - |
| Identifier | https://doi.org/10.1007/s10994-008-5069-3 | - |
| Language | en | - |
| Extent | 14 | en |
| Title | Rollout sampling approximate policy iteration | en |
| Creator | Dimitrakakis Christos | en |
| Creator | Lagoudakis Michael | en |
| Creator | Λαγουδακης Μιχαηλ | el |
| Publisher | Springer Verlag | en |
| Description | Δημοσίευση σε επιστημονικό περιοδικό | el |
| Content Summary | Several researchers have recently investigated the connection between reinforcement learning and classification. We are motivated by proposals of approximate policy iteration schemes without value functions, which focus on policy representation using classifiers and address policy learning as a supervised learning problem. This paper proposes variants of an improved policy iteration scheme which addresses the core sampling problem in evaluating a policy through simulation as a multi-armed bandit machine. The resulting algorithm offers comparable performance to the previous algorithm achieved, however, with significantly less computational effort. An order of magnitude improvement is demonstrated experimentally in two standard reinforcement learning domains: inverted pendulum and mountain-car. | en |
| Type of Item | Peer-Reviewed Journal Publication | en |
| Type of Item | Δημοσίευση σε Περιοδικό με Κριτές | el |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2015-10-27 | - |
| Date of Publication | 2008 | - |
| Subject | Reinforcement learning | en |
| Subject | Approximate policy iteration | en |
| Subject | Rollouts | en |
| Subject | Bandit problems | en |
| Subject | Classification | en |
| Subject | Sample complexity | en |
| Bibliographic Citation | C. Dimitrakakis and M. G. Lagoudakis "Rollout sampling approximate policy iteration," Machine Learning, vol. 72, no. 3, pp. 157-171, Sept. 2008. doi: 10.1007/s10994-008-5069-3 | en |
Copyright © DIAS 2013
