Recent research advances in Reinforcement Learning in Spoken Dialogue Systems
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| Publicado en: | The Knowledge Engineering Review vol. 24, no. 4 (Dec 2009), p. 375-408 |
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Cambridge University Press
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| Acceso en línea: | Citation/Abstract Full Text - PDF |
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| 100 | 1 | |a Frampton, Matthew | |
| 245 | 1 | |a Recent research advances in Reinforcement Learning in Spoken Dialogue Systems | |
| 260 | |b Cambridge University Press |c Dec 2009 | ||
| 513 | |a Feature | ||
| 520 | 3 | |a This paper will summarize and analyze the work of the different research groups who have recently made significant contributions in using Reinforcement Learning techniques to learn dialogue strategies for Spoken Dialogue Systems (SDSs). This use of stochastic planning and learning has become an important research area in the past 10 years, since it promises automatic data-driven optimization of the behavior of SDSs that were previously hand-coded by expert developers. We survey the most important developments in the field, compare and contrast the different approaches, and describe current open problems. [PUBLICATION ABSTRACT] | |
| 653 | |a Information technology | ||
| 653 | |a User interface | ||
| 653 | |a Voice recognition | ||
| 653 | |a Machine learning | ||
| 653 | |a Research | ||
| 653 | |a Simulation | ||
| 653 | |a Design | ||
| 653 | |a Probability | ||
| 653 | |a Markov analysis | ||
| 653 | |a Interactive computer systems | ||
| 653 | |a Artificial intelligence | ||
| 700 | 1 | |a Lemon, Oliver | |
| 773 | 0 | |t The Knowledge Engineering Review |g vol. 24, no. 4 (Dec 2009), p. 375-408 | |
| 786 | 0 | |d ProQuest |t ABI/INFORM Global | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/217516248/abstract/embedded/160PP4OP4BJVV2EV?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/217516248/fulltextPDF/embedded/160PP4OP4BJVV2EV?source=fedsrch |