{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T16:11:13Z","timestamp":1784736673461,"version":"3.55.0"},"reference-count":6,"publisher":"MIT Press - Journals","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Evolutionary Computation"],"published-print":{"date-parts":[[2003,9]]},"abstract":"<jats:p> Recently, Learning Classifier Systems (LCS) and particularly XCS have arisen as promising methods for classification tasks and data mining. This paper investigates two models of accuracy-based learning classifier systems on different types of classification problems. Departing from XCS, we analyze the evolution of a complete action map as a knowledge representation. We propose an alternative, UCS, which evolves a best action map more efficiently. We also investigate how the fitness pressure guides the search towards accurate classifiers. While XCS bases fitness on a reinforcement learning scheme, UCS defines fitness from a supervised learning scheme. We find significant differences in how the fitness pressure leads towards accuracy, and suggest the use of a supervised approach specially for multi-class problems and problems with unbalanced classes. We also investigate the complexity factors which arise in each type of accuracy-based LCS. We provide a model on the learning complexity of LCS which is based on the representative examples given to the system. The results and observations are also extended to a set of real world classification problems, where accuracy-based LCS are shown to perform competitively with respect to other learning algorithms. The work presents an extended analysis of accuracy-based LCS, gives insight into the understanding of the LCS dynamics, and suggests open issues for further improvement of LCS on classification tasks. <\/jats:p>","DOI":"10.1162\/106365603322365289","type":"journal-article","created":{"date-parts":[[2003,9,20]],"date-time":"2003-09-20T08:09:38Z","timestamp":1064045378000},"page":"209-238","source":"Crossref","is-referenced-by-count":291,"title":["Accuracy-Based Learning Classifier Systems: Models, Analysis and Applications to Classification Tasks"],"prefix":"10.1162","volume":"11","author":[{"given":"Ester","family":"Bernad\u00f3-Mansilla","sequence":"first","affiliation":[{"name":"Enginyeria i Arquitectura La Salle, Ramon Llull University, Passeig Bonanova, 8. 08022 Barcelona, Spain"},{"name":"Computing Sciences, Bell Laboratories, Lucent Technologies, 600-700 Mountain Avenue, Murray Hill, NJ 07974-0636, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Josep M.","family":"Garrell-Guiu","sequence":"additional","affiliation":[{"name":"Enginyeria i Arquitectura La Salle, Ramon Llull University, Passeig Bonanova, 8. 08022 Barcelona, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"281","reference":[{"key":"p_7","first-page":"568","author":"Bull L.","year":"2002","journal-title":"J. L., and Schwefer, H.-P., editors, Parallel Problem Solving from Nature - PPSN VII, pages"},{"key":"p_11","doi-asserted-by":"publisher","DOI":"10.1177\/105971239400300201"},{"key":"p_13","doi-asserted-by":"publisher","DOI":"10.1162\/089976698300017197"},{"key":"p_15","doi-asserted-by":"publisher","DOI":"10.1007\/BF00114162"},{"key":"p_32","doi-asserted-by":"publisher","DOI":"10.1007\/BF00058679"},{"key":"p_33","doi-asserted-by":"publisher","DOI":"10.1162\/evco.1995.3.2.149"}],"container-title":["Evolutionary Computation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mitpressjournals.org\/doi\/pdf\/10.1162\/106365603322365289","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,3,12]],"date-time":"2021-03-12T21:30:44Z","timestamp":1615584644000},"score":1,"resource":{"primary":{"URL":"https:\/\/direct.mit.edu\/evco\/article\/11\/3\/209-238\/1152"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2003,9]]},"references-count":6,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2003,9]]}},"alternative-id":["10.1162\/106365603322365289"],"URL":"https:\/\/doi.org\/10.1162\/106365603322365289","relation":{},"ISSN":["1063-6560","1530-9304"],"issn-type":[{"value":"1063-6560","type":"print"},{"value":"1530-9304","type":"electronic"}],"subject":[],"published":{"date-parts":[[2003,9]]}}}