{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T07:08:23Z","timestamp":1761894503418},"publisher-location":"Berlin, Heidelberg","reference-count":36,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783540497721"},{"type":"electronic","value":"9783540497745"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2007]]},"DOI":"10.1007\/978-3-540-49774-5_7","type":"book-chapter","created":{"date-parts":[[2007,4,2]],"date-time":"2007-04-02T16:18:34Z","timestamp":1175530714000},"page":"153-178","source":"Crossref","is-referenced-by-count":10,"title":["Evolutionary Online Data Mining: An Investigation in a Dynamic Environment"],"prefix":"10.1007","author":[{"given":"Hai H.","family":"Dam","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chris","family":"Lokan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hussein A.","family":"Abbass","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","reference":[{"key":"7_CR1_7","unstructured":"H. A. Abbass, J. Bacardit, M. V. Butz, and X. Llora. Online Adaptation in Learning Classifier Systems: Stream Data Mining. Illinois Genetic Algorithms Laboratory, University of Illinois at Urbana-Champaign, June 2004. IlliGAL Report No. 2004031."},{"key":"7_CR2_7","unstructured":"J. Bacardit and M. V. Butz. Data Mining in Learning Classifier Systems: Com- paring XCS with GAssist. Illinois Genetic Algorithms Laboratory, University of Illinois at Urbana-Champaign, June 2004. IlliGAL Report No. 2004030."},{"key":"7_CR3_7","unstructured":"E. Bernad\u00f3, X. Llor\u00e0, and J. M. Garrell. XCS and GALE: a comparative study of two learning classifier systems with six other learning algorithms on classi- fication tasks. In Proceedings of the 4th International Workshop on Learning Classifier Systems (IWLCS-2001), pages 337-341, 2001. Short version published in Genetic and Evolutionary Compution Conference (GECCO2001)."},{"key":"7_CR4_7","doi-asserted-by":"crossref","unstructured":"J. Branke. Evolutionary Optimization in Dynamic Environments, volume 3 of Genetic Algorithms and Evolutionary Computation. Kluwer Academic Publish- ers, 2002.","DOI":"10.1007\/978-1-4615-0911-0"},{"key":"7_CR5_7","unstructured":"M. V. Butz. Rule-based Evolutionary Online Learning Systems: Learning Bounds, Classification, and Prediction. PhD thesis, University of Illinois at Urbana-Champaign, 2004."},{"key":"7_CR6_7","unstructured":"M. V. Butz, T. Kovacs, P. L. Lanze, and S. W. Wilson. Toward a theory of generalization and learning in XCS. IEEE Tranactions on Evolutionary Computation, 7(6), 2003."},{"key":"7_CR7_7","doi-asserted-by":"crossref","unstructured":"M. V. Butz and S. W. Wilson. An algorithmic description of XCS. In IWLCS \u201900: Revised Papers from the Third International Workshop on Advances in Learning Classifier Systems, pages 253-272. Springer-Verlag, 2001.","DOI":"10.1007\/3-540-44640-0_15"},{"key":"7_CR8_7","doi-asserted-by":"crossref","unstructured":"H. H. Dam, H. A. Abbass, and C. Lokan. DXCS: an XCS system for distrib- uted data mining. In Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2005, Washington D.C., USA, 2005.","DOI":"10.1145\/1068009.1068326"},{"key":"7_CR9_7","unstructured":"H. H. Dam, H. A. Abbass, and C. Lokan. Investigation on DXCS: An XCS system for distribution data mining, with continuous-valued inputs in static and dynamic environments. In Proceedings of IEEE Cogress on Evolutionary Computation, Edinburgh, Scotland, 2005."},{"issue":"2-3","key":"7_CR10_7","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1007\/BF00993042","volume":"13","author":"KA De Jong","year":"1993","unstructured":"K. A. De Jong, W. M. Spears, and D. F. Gordon. Using genetic algorithms for concept learning. Machine Learning, 13(2-3):161-188, 1993.","journal-title":"Machine Learning"},{"issue":"4-5","key":"7_CR11_7","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1016\/j.knosys.2004.10.002","volume":"18","author":"S Delany","year":"2005","unstructured":"S. Delany, P. Cunningham, A. Tsymbal, and L. Coyle. A case-based technique for tracking concept drift in spam filtering. Journal of Knowledge Based Systems, 18(4-5):187-195, 2005.","journal-title":"Journal of Knowledge Based Systems"},{"key":"7_CR12_7","first-page":"133","volume-title":"Advances in Learning Classifier Systems: 4th International Workshop, IWLCS","author":"PW Dixon","year":"2001","unstructured":"P. W. Dixon, D. Corne, and M. J. Oates. A preliminary investigation of mod- ified XCS as a generic data mining tool. In Advances in Learning Classifier Systems: 4th International Workshop, IWLCS, pages 133-150. Berlin Heidel- berg: Springer-Verlag, 2001."},{"key":"7_CR13_7","unstructured":"C. B. D. J. Newman, S. Hettich and C. Merz. UCI repository of machine learning databases. University of California, Irvine, Department of Information and Com- puter Sciences. http:\/\/www.ics.uci.edu\/\u223cmlearn\/MLRepository.html , 1998."},{"key":"7_CR14_7","unstructured":"U. Fayyad, G. Piatetsky-Shapiro, P. Smyth, and R. Uthurusamy. From data mining to knowledge discovery: An overview. In Advances in Knowledge Discovery and Data Mining, pages 1-36. The MIT Press, 1996."},{"key":"7_CR15_7","unstructured":"D. E. Goldberg. Computer-Aided Gas Pipeline Operation using Genetic Algo- rithms and Rule Learning. PhD thesis, The University of Michigan, 1983."},{"key":"7_CR16_7","volume-title":"Genetic Algorithms in Search, Optimization, and Machine Learning","author":"DE Goldberg","year":"1989","unstructured":"D. E. Goldberg. Genetic Algorithms in Search, Optimization, and Machine Learning. Addision-Wesley Publishing Company, INC., 1989."},{"issue":"2","key":"7_CR17_7","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1023\/A:1007420529897","volume":"32","author":"MB Harries","year":"1998","unstructured":"M. B. Harries, C. Sammut, and K. Horn. Extracting hidden context. Machine Learning, 32(2):101-126, 1998.","journal-title":"Machine Learning"},{"key":"7_CR18_7","doi-asserted-by":"crossref","unstructured":"J. H. Holland. Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor, 1975. Republished by the MIT press, 1992.","DOI":"10.7551\/mitpress\/1090.001.0001"},{"key":"7_CR19_7","unstructured":"J. H. Holland. Escaping Brittleness: The Possibilities of General-Purpose Learn- ing Algorithms Applied to Parallel Rule-Based Systems. In Mitchell, Michalski, and Carbonell, editors, Machine Learning, an Artificial Intelligence Approach. Volume II, chapter 20, pages 593-623. Morgan Kaufmann, 1986."},{"key":"7_CR20_7","volume-title":"Pattern-directed In- ference Systems","author":"JH Holland","year":"1978","unstructured":"J. H. Holland, and J. S. Reitman. Cognitive systems based on adaptive algo- rithms. In D. A. Waterman and F. Hayes-Roth, editors, Pattern-directed In- ference Systems. New York: Academic Press, 1978. Reprinted in: Evolutionary Computation. The Fossil Record. David B. Fogel (Ed.) IEEE Press, 1998. isbn: 0-7803-3481-7."},{"key":"7_CR21_7","unstructured":"R. Klinkenberg and T. Joachims. Detecting concept drift with support vector machines. In ICML \u201900: Proceedings of the Seventeenth International Conference on Machine Learning, pages 487-494, San Francisco, CA, USA, 2000. Morgan Kaufmann Publishers Inc."},{"key":"7_CR22_7","doi-asserted-by":"crossref","unstructured":"J. Kolter and M. Maloof. Dynamic weighted majority: A new ensemble method for tracking concept drift. In Proceedings of the Third IEEE International Con- ference on Data Mining, pages 123-130, Los Alamitos, CA, 2003. IEEE Press.","DOI":"10.1109\/ICDM.2003.1250911"},{"key":"7_CR23_7","doi-asserted-by":"crossref","unstructured":"T. Kovacs. XCS classifier system reliably evolves accurate, complete, and min- imal representations for boolean functions. In C. Roy and Pant, editors, Soft Computing in Engineering Design and Manufacturing (WSC2), pages 59-68. Springer-Verlag, 1997.","DOI":"10.1007\/978-1-4471-0427-8_7"},{"key":"7_CR24_7","first-page":"367","volume-title":"Fourth International Workshop on Learning Classifier Systems - IWLCS-2001","author":"T Kovacs","year":"2001","unstructured":"T. Kovacs. Two views of classifier systems. In Fourth International Workshop on Learning Classifier Systems - IWLCS-2001, pages 367-371, San Francisco, California, USA, 7 2001."},{"key":"7_CR25_7","unstructured":"25. P. L. Lanzi and M. Colombetti. An extension to the XCS classifier system for stochastic environments, 1999."},{"key":"7_CR26_7","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1007\/3-540-45027-0_12","volume-title":"Learning Classifier Systems, From Foundations to Applications","author":"S Saxon","year":"2000","unstructured":"S. Saxon, and A. Barry. XCS and the Monk\u2019s problems. In Learning Classifier Systems, From Foundations to Applications, pages 223-242, London, UK, 2000. Springer-Verlag."},{"key":"7_CR27_7","unstructured":"J. C. Schlimmer and D.H. Fisher. A case study of incremental concept induction. In Proceedings of the Fifth National Conference on Artificial Intelligence, pages 496-501, Philadelpha, PA, 1986. Morgan Kaufmann."},{"key":"7_CR28_7","unstructured":"S. F. Smith. A Learning System Based on Genetic Adaptive Algorithms. PhD thesis, University of Pittsburgh, 1980."},{"issue":"3","key":"7_CR29_7","doi-asserted-by":"publisher","first-page":"299","DOI":"10.1162\/106365603322365315","volume":"11","author":"C Stone","year":"2003","unstructured":"C. Stone and L. Bull. For real! XCS with continuous-valued inputs. Evolutionary Computation, 11(3):299-336, 2003.","journal-title":"Evolutionary Computation"},{"key":"7_CR30_7","doi-asserted-by":"crossref","unstructured":"W. N. Street and Y. Kim. A streaming ensemble algorithm (sea) for large- scale classification. In KDD \u201901: Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining, pages 377- 382, New York, NY, USA, 2001. ACM Press.","DOI":"10.1145\/502512.502568"},{"key":"7_CR31_7","doi-asserted-by":"crossref","unstructured":"H. Wang, W. Fan, P. S. Yu, and J. Han. Mining concept-drifting data streams using ensemble classifiers. In KDD \u201903: Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining, pages 226- 235, New York, NY, USA, 2003. ACM Press.","DOI":"10.1145\/956750.956778"},{"issue":"1","key":"7_CR32_7","first-page":"69","volume":"23","author":"G Widmer","year":"1996","unstructured":"G. Widmer and M. Kubat. Learning in the presence of concept drift and hidden contexts. Machine Learning, 23(1):69-101, 1996.","journal-title":"Machine Learning"},{"key":"7_CR33_7","unstructured":"S. W. Wilson. Knowledge Growth in an Artificial Animal. In Proceedings of the First International Conference on Genetic Algorithms and their Applications, pages 16-23. Lawrence Erlbaum Associates, 1985."},{"issue":"2","key":"7_CR34_7","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1162\/evco.1995.3.2.149","volume":"3","author":"SW Wilson","year":"1995","unstructured":"S. W. Wilson. Classifier fitness based on accuracy. Evolutionary Computation, 3(2):149-175, 1995.","journal-title":"Evolutionary Computation"},{"key":"7_CR35_7","unstructured":"S. W. Wilson. Generalization in the XCS classifier system. In J. R. Koza, W. Banzhaf, K. Chellapilla, K. Deb, M. Dorigo, D. B. Fogel, M. H. Garzon, D. E. Goldberg, H. Iba, and R. Riolo, editors, Genetic Programming 1998: Proceedings of the Third Annual Conference, pages 665-674, University of Wisconsin, Madison, Wisconsin, USA, 1998. Morgan Kaufmann."},{"key":"7_CR36_7","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1007\/3-540-45027-0_11","volume-title":"Learning Classifier Systems, From Foun- dations to Applications, LNAI-1813","author":"SW Wilson","year":"2000","unstructured":"S. W. Wilson. Get real! XCS with continuous-valued inputs. In P. Lanzi, W. Stolzmann, and S. Wilson, editors, Learning Classifier Systems, From Foun- dations to Applications, LNAI-1813, pages 209-219, Berlin, 2000. Springer- Verlag."}],"container-title":["Studies in Computational Intelligence","Evolutionary Computation in Dynamic and Uncertain Environments"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-540-49774-5_7.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,11,19]],"date-time":"2020-11-19T05:07:33Z","timestamp":1605762453000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-540-49774-5_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2007]]},"ISBN":["9783540497721","9783540497745"],"references-count":36,"URL":"https:\/\/doi.org\/10.1007\/978-3-540-49774-5_7","relation":{},"ISSN":["1860-949X","1860-9503"],"issn-type":[{"type":"print","value":"1860-949X"},{"type":"electronic","value":"1860-9503"}],"subject":[],"published":{"date-parts":[[2007]]}}}