Abstract
PANIC (Parallelism And Neural networks In Classifier systems), an Evolutionary Rule Based System (ERBS) to evolve behavioral strategies codified by sets of rules, is presented. PANIC assigns credit to the rules through a new mechanism, Q-Credit Assignment (QCA), based on Q-learning. By taking into account the context where a rule is applied, QCA is more accurate than classical methods when a single rule can fire in different situations. QCA is implemented through a multi-layer feed-forward neural network.
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© 1994 Springer-Verlag Berlin Heidelberg
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Giani, A., Baiardi, F., Starita, A. (1994). Q-learning in Evolutionary Rule Based Systems. In: Davidor, Y., Schwefel, HP., Männer, R. (eds) Parallel Problem Solving from Nature — PPSN III. PPSN 1994. Lecture Notes in Computer Science, vol 866. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58484-6_271
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DOI: https://doi.org/10.1007/3-540-58484-6_271
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