caa a22 4500 467943338 CHVBK 20180323165659.0 cr unu---uuuuu 170328e19881001xx s 000 0 eng 10.1007/BF00113898 doi (NATIONALLICENCE)springer-10.1007/BF00113898 (NATIONALLICENCE)springer-10.1023/A:1022614421909 Grefenstette John Navy Center for Applied Research in Artificial Intelligence, Naval Research Laboratory, 20375-5000, Washington, DC, U.S.A. aut Credit assignment in rule discovery systems based on genetic algorithms [Elektronische Daten] [John Grefenstette] In rule discovery systems, learning often proceeds by first assessing the quality of the system's current rules and then modifying rules based on that assessment. This paper addresses the credit assignment problem that arises when long sequences of rules fire between successive external rewards. The focus is on the kinds of rule assessment schemes which have been proposed for rule discovery systems that use genetic algorithms as the primary rule modification strategy. Two distinct approaches to rule learning with genetic algorithms have been previously reported, each approach offering a useful solution to a different level of the credit assignment problem. We describe a system, called RUDI, that exploits both approaches. We present analytic and experimental results that support the hypothesis that multiple levels of credit assignment can improve the performance of rule learning systems based on genetic algorithms. Kluwer Academic Publishers, 1988 Credit assignment nationallicence rule discovery nationallicence genetic algorithms nationallicence classifier systems nationallicence bucket brigade algorithm nationallicence Machine Learning Kluwer Academic Publishers 3/2-3(1988-10-01), 225-245 0885-6125 3:2-3<225 1988 3 10994 https://doi.org/10.1007/BF00113898 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/BF00113898 text/html Onlinezugriff via DOI NATIONALLICENCE 773 0- Machine Learning Kluwer Academic Publishers 3/2-3(1988-10-01), 225-245 0885-6125 3:2-3<225 1988 3 10994 NATIONALLICENCE 100 1- Grefenstette John Navy Center for Applied Research in Artificial Intelligence, Naval Research Laboratory, 20375-5000, Washington, DC, U.S.A aut NATIONALLICENCE 856 40 https://doi.org/10.1023/A:1022614421909 text/html Onlinezugriff via DOI NATIONALLICENCE 773 0- Machine Learning Kluwer Academic Publishers-Plenum Publishers 3/2-3(1988-10-01), 225-245 0885-6125 3:2-3<225 1988 3 10994 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE NATIONALLICENCE NL-springer