메뉴 건너뛰기




Volumn 52, Issue 2-3, 2005, Pages 148-159

Evolution of recurrent neural controllers using an extended parallel genetic algorithm

Author keywords

Mobile robot; Multi population genetic algorithm; Recurrent neural network; Sequential task

Indexed keywords

COMPUTER SIMULATION; CONTROL EQUIPMENT; GENETIC ALGORITHMS; INTELLIGENT AGENTS; INTELLIGENT ROBOTS; MOBILE ROBOTS; POPULATION STATISTICS; ROBOT LEARNING;

EID: 22644434133     PISSN: 09218890     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.robot.2005.04.003     Document Type: Article
Times cited : (22)

References (21)
  • 3
    • 0030167565 scopus 로고    scopus 로고
    • An incremental approach to developing intelligent neural controllers for robots
    • L.A. Meeden An incremental approach to developing intelligent neural controllers for robots IEEE Trans. Syst. Man Cybern. 26 1996 474 485
    • (1996) IEEE Trans. Syst. Man Cybern. , vol.26 , pp. 474-485
    • Meeden, L.A.1
  • 4
    • 0035650666 scopus 로고    scopus 로고
    • Evolution of adaptive synapses: Robots with fast adaptive behavior in new environments
    • J. Urzelai, and D. Floreano Evolution of adaptive synapses: robots with fast adaptive behavior in new environments Evol. Comput. 9 2001 495 524
    • (2001) Evol. Comput. , vol.9 , pp. 495-524
    • Urzelai, J.1    Floreano, D.2
  • 5
    • 0037591741 scopus 로고    scopus 로고
    • An evolutionary ecological approach to the study learning behavior using a robot-based model
    • E. Tuci, M. Quinn, and I. Harvey An evolutionary ecological approach to the study learning behavior using a robot-based model Adapt. Behav. 10 2002 201 221
    • (2002) Adapt. Behav. , vol.10 , pp. 201-221
    • Tuci, E.1    Quinn, M.2    Harvey, I.3
  • 6
    • 0024875962 scopus 로고
    • Adaptive neural oscillator using continuous-time backpropagation learning
    • K. Doya, and S. Yoshizawa Adaptive neural oscillator using continuous-time backpropagation learning Neural Netw. 2 3 1989 375 386
    • (1989) Neural Netw. , vol.2 , Issue.3 , pp. 375-386
    • Doya, K.1    Yoshizawa, S.2
  • 7
    • 0001202597 scopus 로고
    • Learning state space trajectories in recurrent neural networks
    • B.A. Pearlmutter Learning state space trajectories in recurrent neural networks Neural Comput. 1 2 1989 263 269
    • (1989) Neural Comput. , vol.1 , Issue.2 , pp. 263-269
    • Pearlmutter, B.A.1
  • 8
    • 0001202594 scopus 로고
    • A learning algorithm for continually running fully recurrent neural networks
    • R.J. Williams, and D. Zipser A learning algorithm for continually running fully recurrent neural networks Neural Comput. 1 2 1989 270 280
    • (1989) Neural Comput. , vol.1 , Issue.2 , pp. 270-280
    • Williams, R.J.1    Zipser, D.2
  • 9
    • 0028392483 scopus 로고
    • Learning long-term dependencies with gradient descent is difficult
    • Y. Bengio, P. Simard, and P. Frasconi Learning long-term dependencies with gradient descent is difficult IEEE Trans. Neural Netw. 5 2 1994 157 166
    • (1994) IEEE Trans. Neural Netw. , vol.5 , Issue.2 , pp. 157-166
    • Bengio, Y.1    Simard, P.2    Frasconi, P.3
  • 11
    • 0001033889 scopus 로고
    • Learning complex extended sequences using the principle of history compression
    • J. Schmidhuber Learning complex extended sequences using the principle of history compression Neural Comput. 4 2 1992 234 242
    • (1992) Neural Comput. , vol.4 , Issue.2 , pp. 234-242
    • Schmidhuber, J.1
  • 12
    • 0035462333 scopus 로고    scopus 로고
    • Simple recurrent networks learn context-free and context-sensitive languages by counting
    • P. Rodriguez Simple recurrent networks learn context-free and context-sensitive languages by counting Neural Comput. 13 9 2001 2093 2118
    • (2001) Neural Comput. , vol.13 , Issue.9 , pp. 2093-2118
    • Rodriguez, P.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.