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Performance Comparison of Two Reinforcement Learning Algorithms for Small Mobile Robots
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SYSNO ASEP 0331131 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve SCOPUS Title Performance Comparison of Two Reinforcement Learning Algorithms for Small Mobile Robots Title Srovnání efektivity dvou algoritmů posilovaného učení pro malé mobilní roboty Author(s) Neruda, Roman (UIVT-O) SAI, RID, ORCID
Slušný, Stanislav (UIVT-O)Source Title International Journal of Control and Automation - ISSN 2005-4297
Roč. 2, č. 1 (2009), s. 59-68Number of pages 10 s. Language eng - English Country KR - Korea, Republic of Keywords reinforcement learning ; mobile robots ; inteligent agents Subject RIV IN - Informatics, Computer Science R&D Projects 1M0567 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) CEZ AV0Z10300504 - UIVT-O (2005-2011) EID SCOPUS 80051745242 Annotation The design of intelligent agents by means of reinforcement learning is studied in this paper. A relational reinforcement learning algorithm is used to achieve a compact knowledge representation. Moreover, this approach allows to improve the learning performance by augmenting the algorithm with the so-called background knowledge. A case study on simulated physical robotic agents is performed and compared with our previous evolutionary robotics experiments in order to justify our approach. Workplace Institute of Computer Science Contact Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Year of Publishing 2010
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