Abstract
To study the relevance of recurrent neural network structures for the behavior of autonomous agents a series of experiments with miniature robots is performed. A special evolutionary algorithm is used to generate netw orks of different sizes and architectures. Solutions for obstacle a voidance and phototropic behavior are presented. Networks are evolved with the help of simulated robots, and the results are validated with the use of physical robots.
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References
Husbands, P., and Harwey, I. (1992) Evolution versus design: Controlling autonomous robots, in: Integrating perception, planning and action: Proceedings of the Third Annual Conferences on Artificial Intelligence, IEEE Press, Los Alamitos.
Michel, O., Khepera Simulator Package version 2.0: Freeware mobile robot simulator written at the University of Nice Sophia-Antipolis by Oliver Michel. Downloadable from the World Wide Web at http://wwwi3s.unice.fr/~om/khep-sim.html
Mondala, F., Franzi, E., and Ienne, P. (1993), Mobile robots miniturization: a tool for investigation in control algorithms, in: Proceedings of ISER'’93, Kyoto, October 1993.
Nolfi, S., and Floreano, D. (2000) Evolutionary Robotics: The Biology, Intelligence, and Technology of Self-Organizing Machines MIT Press, Cambridge.
Pasemann, F. (1993), Dynamics of a single model neuron, International Journal of Bifurcation and Chaos, 2, 271–278.
Pasemann, F. (1998), Evolving neurocontrollers for balancing an inverted pendulum, Network: Computation in Neural Systems, 9, 495–511.
Pfeifer, R., and Scheier, C. (2000), Understanding Intelligence, MIT Press, Cambridge.
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© 2001 Springer-Verlag Berlin Heidelberg
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Pasemann, F., Steinmetz, U., Hülse, M., Lara2, B. (2001). Evolving Brain Structures for Robot Control. In: Mira, J., Prieto, A. (eds) Bio-Inspired Applications of Connectionism. IWANN 2001. Lecture Notes in Computer Science, vol 2085. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45723-2_49
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DOI: https://doi.org/10.1007/3-540-45723-2_49
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