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Volumn , Issue , 2004, Pages 791-798

Interpolation-based Q-learning

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; COMPUTER SIMULATION; CONVERGENCE OF NUMERICAL METHODS; DYNAMIC PROGRAMMING; FUNCTIONS; INTERPOLATION; MARKOV PROCESSES; PROBLEM SOLVING; Q FACTOR MEASUREMENT; TRIANGULATION;

EID: 14344263882     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (55)

References (10)
  • 2
    • 84880694195 scopus 로고
    • Stable function approximation in dynamic programming
    • Morgan Kaufmann
    • Gordon, G. J. (1995). Stable function approximation in dynamic programming. Proc. of ICML 20 (pp. 261-268). Morgan Kaufmann.
    • (1995) Proc. of ICML , vol.20 , pp. 261-268
    • Gordon, G.J.1
  • 3
    • 85014758967 scopus 로고    scopus 로고
    • Estimation of the density and the regression function under mixing conditions
    • Liebscher, E. (2001). Estimation of the density and the regression function under mixing conditions. Statistics & Decisions, 19, 9-26.
    • (2001) Statistics & Decisions , vol.19 , pp. 9-26
    • Liebscher, E.1
  • 5
    • 84880680664 scopus 로고    scopus 로고
    • Variable resolution discretization for high-accuracy solutions of optimal control problems
    • Munos, R., &: Moore, A. (1999). Variable resolution discretization for high-accuracy solutions of optimal control problems. Proc. of IJCAI (pp. 1348-1355).
    • (1999) Proc. of IJCAI , pp. 1348-1355
    • Munos, R.1    Moore, A.2
  • 6
    • 0036832956 scopus 로고    scopus 로고
    • Kernel-based reinforcement learning
    • Ormoneit, D., & Sen, S. (2002). Kernel-based reinforcement learning. Machine Learning, 49, 161-178.
    • (2002) Machine Learning , vol.49 , pp. 161-178
    • Ormoneit, D.1    Sen, S.2
  • 7
    • 85153965130 scopus 로고
    • Reinforcement learning with soft state aggregation
    • MIT Press
    • Singh, S., Jaakkola, T., & Jordan, M. (1995). Reinforcement learning with soft state aggregation. NIPS 7 (pp. 361-368). MIT Press.
    • (1995) NIPS , vol.7 , pp. 361-368
    • Singh, S.1    Jaakkola, T.2    Jordan, M.3
  • 8
    • 0029753630 scopus 로고    scopus 로고
    • Reinforcement learning with replacing eligibility traces
    • Singh, S., &: Sutton, R. (1996). Reinforcement learning with replacing eligibility traces. Machine Learning, 32, 123-158.
    • (1996) Machine Learning , vol.32 , pp. 123-158
    • Singh, S.1    Sutton, R.2
  • 9
    • 0033570798 scopus 로고    scopus 로고
    • A unified analysis of value-function-based reinforcement-learning algorithms
    • Szepesvári, C., & Littman, M. (1999). A unified analysis of value-function-based reinforcement-learning algorithms. Neural Computation, 11, 2017-2059.
    • (1999) Neural Computation , vol.11 , pp. 2017-2059
    • Szepesvári, C.1    Littman, M.2
  • 10
    • 0029752470 scopus 로고    scopus 로고
    • Feature-based methods for large scale dynamic programming
    • Tsitsiklis, J. N., & Van Roy, B. (1996). Feature-based methods for large scale dynamic programming. Machine Learning, 22, 59-94.
    • (1996) Machine Learning , vol.22 , pp. 59-94
    • Tsitsiklis, J.N.1    Van Roy, B.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.