Mpi Tr-060
نویسندگان
چکیده
Evolutionary optimization of sensorimotor control has lead to matched lter neurons in the visual system of ies that are specialized to certain visual motion patterns. We apply the technique of genetic algorithms in order to model parts of the sensor system and behavior of an arti cial agent. The agents are rather simple systems with only four sensors. We will show how genetic algorithms can be applied to evolve simple matched lters that analyze the visual motion information for the task of obstacle avoidance. We compare the agents' sensorimotor control to that of ies. Further we test the optimization performance of the genetic algorithms. We can show that the use of binary or Gray coding has no signi cant in uence on our optimization results and the speed of convergence. Real value coding leads on average to slightly smaller maximal tness values. The use of a combination of mutation and crossover leads to high tness individuals and a high tness population.
منابع مشابه
CEWES MSRC / PET TR / 98 - 02 Review of Performance Analysis Tools for MPI Parallel Programs
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Views, opinions and/or findings contained in this report are those of the author(s) and should not be construed as an official Department of Defense Position, policy, or decision unless so designated by other official documentation.
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