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Volumn , Issue , 2011, Pages 737-744

Structure learning in ergodic factored MDPs without knowledge of the transition function's in-degree

Author keywords

[No Author keywords available]

Indexed keywords

EMPIRICAL RESULTS; ERGODICS; IN-DEGREE; MODEL-BASED OPC; PLANNING HORIZONS; PRIOR KNOWLEDGE; SAMPLE COMPLEXITY; STRUCTURE LEARNING ALGORITHM; STRUCTURE-LEARNING; TRANSITION FUNCTIONS;

EID: 80053436895     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (38)

References (9)
  • 1
    • 0041965975 scopus 로고    scopus 로고
    • R-max - A general polynomial time algorithm for near-optimal reinforcement learning
    • Brafman, Ronen I. and Tennenholtz, Moshe. R-max - a general polynomial time algorithm for near-optimal reinforcement learning. Journal of Machine Learning Research, 3:213-231, 2003.
    • (2003) Journal of Machine Learning Research , vol.3 , pp. 213-231
    • Brafman, R.I.1    Tennenholtz, M.2
  • 3
    • 71149108881 scopus 로고    scopus 로고
    • The adaptive k-meteorologists problem and its application to structure learning and feature selection in reinforcement learning
    • Diuk, Carlos, Li, Lihong, and Leffler, Bethany R. The adaptive k-meteorologists problem and its application to structure learning and feature selection in reinforcement learning. In Proceedings of the 26th International Conference on Machine Learning'09, pp. 249-256.
    • Proceedings of the 26th International Conference on Machine Learning'09 , pp. 249-256
    • Diuk, C.1    Li, L.2    Leffler, B.R.3
  • 6
    • 0036832954 scopus 로고    scopus 로고
    • Near-optimal reinforcement learning in polynomial time
    • Kearns, Michael and Singh, Satinder. Near-optimal reinforcement learning in polynomial time. Machine Learning, pp. 209-232, 2002.
    • (2002) Machine Learning , pp. 209-232
    • Kearns, M.1    Singh, S.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.