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Volumn 4131 LNCS - I, Issue , 2006, Pages 830-839

Reinforcement learning with echo state networks

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION THEORY; CONVERGENCE OF NUMERICAL METHODS; DECISION MAKING; MARKOV PROCESSES; NEURAL NETWORKS;

EID: 33749845123     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11840817_86     Document Type: Conference Paper
Times cited : (55)

References (17)
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    • Tutorial on training recurrent neural networks, covering BPTT, RTRL, EKF and the 'echo state network' approach
    • German National Research Center for Information Technology
    • Jaeger, H.: Tutorial on training recurrent neural networks, covering BPTT, RTRL, EKF and the 'echo state network' approach. Technical Report GMD Report 159, German National Research Center for Information Technology (2002)
    • (2002) Technical Report GMD Report , vol.159
    • Jaeger, H.1
  • 4
    • 1842421269 scopus 로고    scopus 로고
    • Harnessing nonlinearity: Predicting chaotic systems and saving energy in wireless telecommunication
    • Jaeger, H., Haas, H.: Harnessing nonlinearity: predicting chaotic systems and saving energy in wireless telecommunication. Science (2004) 78-80
    • (2004) Science , pp. 78-80
    • Jaeger, H.1    Haas, H.2
  • 5
    • 0024702037 scopus 로고
    • A parallel network that learns to play backgammon
    • Tesauro, G., Sejnowski, T.J.: A parallel network that learns to play backgammon. Artificial Intelligence 39 (1989) 357-390
    • (1989) Artificial Intelligence , vol.39 , pp. 357-390
    • Tesauro, G.1    Sejnowski, T.J.2
  • 7
    • 0012331016 scopus 로고
    • Memory approaches to reinforcement learning in nonmarkovian domains
    • Carnegie Mellon University, Pittsburgh, PA
    • Lin, L.J., Mitchell, T.M.: Memory approaches to reinforcement learning in nonmarkovian domains. Technical Report CMU-CS-92-138, Carnegie Mellon University, Pittsburgh, PA (1992)
    • (1992) Technical Report , vol.CMU-CS-92-138
    • Lin, L.J.1    Mitchell, T.M.2
  • 8
    • 26444565569 scopus 로고
    • Finding structure in time
    • Elman, J.L.: Finding structure in time, Cognitive Science 14 (1990) 179-211
    • (1990) Cognitive Science , vol.14 , pp. 179-211
    • Elman, J.L.1
  • 9
    • 4544284544 scopus 로고    scopus 로고
    • Evolution of goal-directed behavior from limited information in a complex environment
    • Orlando, Florida, USA, Morgan Kaufmann
    • Glickman, M.R., Sycara, K.: Evolution of goal-directed behavior from limited information in a complex environment. In: Proc. of the Genetic arid Evol. Comp. Conf., Orlando, Florida, USA, Morgan Kaufmann (1999) 1281-1288
    • (1999) Proc. of the Genetic Arid Evol. Comp. Conf. , pp. 1281-1288
    • Glickman, M.R.1    Sycara, K.2
  • 12
    • 12744249791 scopus 로고
    • Making the world differentiate
    • Institut für Informatik, Technische Universität München
    • Schmidhuber, J.: Making the world differentiate. Technical Report TR-FKI-126-90, Institut für Informatik, Technische Universität München (1990)
    • (1990) Technical Report , vol.TR-FKI-126-90
    • Schmidhuber, J.1
  • 13
    • 85151728371 scopus 로고
    • Residual algorithms: Reinforcement learning with function approximation
    • Baird, L.C.: Residual algorithms: Reinforcement learning with function approximation. In: International Conference on Machine Learning. (1995) 30-37
    • (1995) International Conference on Machine Learning , pp. 30-37
    • Baird, L.C.1
  • 15
    • 84898995808 scopus 로고    scopus 로고
    • Reinforcement learning with function approximation converges to a region
    • Cambridge, MA, MIT Press
    • Gordon, G.J.: Reinforcement learning with function approximation converges to a region. In: Advances in Neural Information Processing Systems. Volume 13., Cambridge, MA, MIT Press (2001) 1040-1046
    • (2001) Advances in Neural Information Processing Systems , vol.13 , pp. 1040-1046
    • Gordon, G.J.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.