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Volumn , Issue , 2007, Pages 259-266

Efficient reinforcement learning through Evolutionary Acquisition of Neural Topologies

Author keywords

[No Author keywords available]

Indexed keywords

CONTROL TASK; EVOLUTIONARY ACQUISITION; GENETIC ENCODING; LEARNING TASKS; NEURAL STRUCTURES;

EID: 84887011679     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (56)

References (9)
  • 1
    • 21244457900 scopus 로고    scopus 로고
    • Robust non-linear control through neuroevolution
    • The University of Texas, Austin, TX 78712, U. S. A
    • F. J. Gomez and R. Miikkulainen. Robust non-linear control through neuroevolution. Technical report, Department of Computer Sciences, The University of Texas, Austin, TX 78712, U. S. A., 2002.
    • (2002) Technical Report, Department of Computer Sciences
    • Gomez, F.J.1    Miikkulainen, R.2
  • 2
    • 26444529967 scopus 로고    scopus 로고
    • Evolving neurocontrollers for balancing an inverted pendulum
    • F. Pasemann. Evolving neurocontrollers for balancing an inverted pendulum. Network: Computation in Neural Systems, 9:495-511, 1998.
    • (1998) Network: Computation In Neural Systems , vol.9 , pp. 495-511
    • Pasemann, F.1
  • 3
    • 84901411269 scopus 로고    scopus 로고
    • R. Sarker, R. Reynolds, H. Abbass, K. C. Tan, B. McKay, D. Essam, and T. Gedeon, editors, Congress on Evolutionary Computation (CEC2003), IEEE Press
    • C. Igel. Neuroevolution for reinforcement learning using evolution strategies. In R. Sarker, R. Reynolds, H. Abbass, K. C. Tan, B. McKay, D. Essam, and T. Gedeon, editors, Congress on Evolutionary Computation (CEC2003), volume 4, pages 2588-2595. IEEE Press, 2003.
    • (2003) Neuroevolution For Reinforcement Learning Using Evolution Strategies , vol.4 , pp. 2588-2595
    • Igel, C.1
  • 4
    • 27144536042 scopus 로고    scopus 로고
    • PhD thesis, Artificial Intelligence Laboratory. The University of Texas at Austin., Austin, TX 78712, U. S. A., August
    • K. O. Stanley. Efficient Evolution of Neural Networks through Complexification. PhD thesis, Artificial Intelligence Laboratory. The University of Texas at Austin., Austin, TX 78712, U. S. A., August 2004.
    • (2004) Efficient Evolution of Neural Networks Through Complexification
    • Stanley, K.O.1
  • 7
    • 0033362601 scopus 로고    scopus 로고
    • Evolving artificial neural networks
    • X. Yao. Evolving artificial neural networks. Proceedings of the IEEE, 87 (9):1423-1447, 1999.
    • (1999) Proceedings of the IEEE , vol.87 , Issue.9 , pp. 1423-1447
    • Yao, X.1
  • 8
    • 0035377566 scopus 로고    scopus 로고
    • Completely derandomized self-adaptation in evolution strategies
    • N. Hansen and A. Ostermeier. Completely derandomized self-adaptation in evolution strategies. Evolutionary Computation, 9 (2):159-195, 2001.
    • (2001) Evolutionary Computation , vol.9 , Issue.2 , pp. 159-195
    • Hansen, N.1    Ostermeier, A.2
  • 9
    • 0012329219 scopus 로고    scopus 로고
    • A comparison between cellular encoding and direct encoding for genetic neural networks
    • In J. R. Koza, D. E. Goldberg, D. B. Fogel, and R. L. Riolo, editors, Standford University, CA, USA, MIT Press
    • F. Gruau, D. Whitley, and L. Pyeatt. A comparison between cellular encoding and direct encoding for genetic neural networks. In J. R. Koza, D. E. Goldberg, D. B. Fogel, and R. L. Riolo, editors, Genetic Programming: Proceedings of the First Annual Conference, pages 81-89, Standford University, CA, USA, 1996. MIT Press.
    • (1996) Genetic Programming: Proceedings of the First Annual Conference, Pages , pp. 81-89
    • Gruau, F.1    Whitley, D.2    Pyeatt, L.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.