Abstract
The purpose of this paper is to explore the effect of adding known amounts of memory to pure reactive systems in a variety of tasks. Using a finite state machine approach, we construct controllers for a simulated robot for five tasks—obstacle avoidance, wall following, exploration, and box pushing—with two sensor configurations using evolutionary computation techniques, and compare the performance of stateless and memory-based controllers. For obstacle avoidance and exploration no significant difference is observed; for wall-following and box pushing, stateless controllers are significantly worse than memory-based but increasing amounts of memory give no significant increase in performance. The need for memory in these cases reflects a need to discriminate sensorimotor contexts to effectively perform the task.
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Kim, D., Hallam, J.C.T. (2001). Mobile Robot Control Based on Boolean Logic with Internal Memory. In: Kelemen, J., Sosík, P. (eds) Advances in Artificial Life. ECAL 2001. Lecture Notes in Computer Science(), vol 2159. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44811-X_60
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DOI: https://doi.org/10.1007/3-540-44811-X_60
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