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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Teixeira, Hugo Tanzarella Bottura, Celso Pascoli |
| Copyright Year | 2015 |
| Description | Author affiliation: State University of Campinas - UNICAMP, School of Electrical and Computer Engineering - FEEC, DSIF-LCSI, Av. Albert Einstein, N. 400 - LE31 - CEP 13081-970, SP, Brazil (Teixeira, Hugo Tanzarella; Bottura, Celso Pascoli) |
| Abstract | This paper proposes a new algorithm for Temporal-Difference (TD) learning using online support vector regression. It benefits from the good generalization properties support vector regression (SVR) has, and also can do incremental learning and automatically track variation of environment with time-varying characteristics. Using the online SVR we can obtain good estimation of value function in TD learning in linear and nonlinear prediction problems. Experimental results demonstrate the effectiveness of the proposed method by comparison with others methods. |
| Starting Page | 318 |
| Ending Page | 323 |
| File Size | 135765 |
| Page Count | 6 |
| File Format | |
| ISBN | 9789897581496 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-07-21 |
| Publisher Place | France |
| Access Restriction | Subscribed |
| Rights Holder | SCITEPRESS |
| Subject Keyword | Support vector machines Temporal Difference Learning Markov processes Online Support Vector Machine Reinforcement Learning Approximation algorithms Prediction algorithms Value Function Approximation Function approximation Kernel Machine Learning |
| Content Type | Text |
| Resource Type | Article |
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