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Neural networks and analog computation beyond the turing limit

Nolfi, S., Using emergent modularity to develop control systems for mobile robots, Adaptive Behavior, 5(3-4), 343, 1997.

Nolfi, S. and Tani, J., Extracting regularities in space and time through a cascade of prediction networks: The case of a mobile robot navigating in a structured environment, Connection Science, 11(2), 125, 1999.

Pomerleau, D. A., Neural Network Perception for Mobile Robot Guidance, Kluwer, Dordrecht, 1993.

Rumelhart, D. E. and McClelland, J., On learning the past tense of English, in Parallel Distributed Processing: Explorations in the Microstructure of Cognition, Volume 2: Psychological and Biological Models, Rumelhart, D. E., McClelland, J., and the PDP Group, Eds., MIT Press, Cambridge, 216, 1986.

Sharkey, N. E., Ed., Robotics and Autonomous Systems, 22(3-4). Special issue on Robot Learning: The New Wave, 1997.

© 2001 by CRC Press LLC

Tani, J., Model-based learning for mobile robot navigation from the dynamical systems perspective, IEEE Transactions on Systems, Man, and Cybernetics, 26(3), 1996.

Tani, J. and Nolfi, S., Learning to perceive the world as articulated: an approach for hierarchical learning in sensory-motor systems, Proceedings of the Fifth International Conference on Simulation of Adaptive Behavior, MIT Press, Cambridge, 1998.

Wilson, S. W., Knowledge growth in an artificial animal, Proceedings of the First International Conference on Genetic Algorithms and Their Applications, Lawrence Erlbaum, Hillsdale, NJ, 16, 1985.

Wilson, S. W., The animat path to AI, in From Animals to Animats_Proceedings of the First International Conference on Simulation of Adaptive Behavior, Meyer, J.-A. and Wilson, S. W., Eds., MIT Press, Cambridge, 15, 1991.

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