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Volumn , Issue , 2013, Pages 1061-1068

Evolving large-scale neural networks for vision-based reinforcement learning

Author keywords

Games; Indirect encodings; Neuroevolution; Reinforcement learning; Vision based TORCS

Indexed keywords

CONTROL NETWORK; CONTROL TASK; GAMES; HIGH DIMENSIONALITY; INDIRECT ENCODINGS; NETWORK WEIGHTS; NEURO EVOLUTIONS; VISION BASED;

EID: 84883060087     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2463372.2463509     Document Type: Conference Paper
Times cited : (142)

References (16)
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    • Generating large-scale neural networks through discovering geometric regularities
    • New York, NY, USA ACM
    • J. Gauci and K. Stanley. Generating large-scale neural networks through discovering geometric regularities. In Proceedings of the Conference on Genetic and Evolutionary Computation, pages 997-1004, New York, NY, USA, 2007. ACM.
    • (2007) Proceedings of the Conference on Genetic and Evolutionary Computation , pp. 997-1004
    • Gauci, J.1    Stanley, K.2
  • 7
    • 0002933170 scopus 로고
    • Designing neural networks using genetic algorithms with graph generation system
    • H. Kitano. Designing neural networks using genetic algorithms with graph generation system. Complex Systems, 4:461-476, 1990.
    • (1990) Complex Systems , vol.4 , pp. 461-476
    • Kitano, H.1
  • 13
    • 0031194381 scopus 로고    scopus 로고
    • Discovering neural nets with low kolmogorov complexity and high generalization capability
    • J. Schmidhuber. Discovering neural nets with low Kolmogorov complexity and high generalization capability. Neural Networks, 10(5):857-873, 1997.
    • (1997) Neural Networks , vol.10 , Issue.5 , pp. 857-873
    • Schmidhuber, J.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.