{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,4]],"date-time":"2024-09-04T14:14:11Z","timestamp":1725459251421},"publisher-location":"Berlin, Heidelberg","reference-count":18,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783540648918"},{"type":"electronic","value":"9783540685159"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[1998]]},"DOI":"10.1007\/bfb0040806","type":"book-chapter","created":{"date-parts":[[2006,2,6]],"date-time":"2006-02-06T08:05:14Z","timestamp":1139213114000},"page":"547-556","source":"Crossref","is-referenced-by-count":4,"title":["Genetic algorithms for belief network inference: The role of scaling and niching"],"prefix":"10.1007","author":[{"given":"Ole J.","family":"Mengshoel","sequence":"first","affiliation":[]},{"given":"David C.","family":"Wilkins","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2005,12,10]]},"reference":[{"key":"53_CR1","unstructured":"J. E. Baker. Reducing bias and inefficiency in the selection algorithm. In Grefenstette [9], pages 14\u201321."},{"key":"53_CR2","first-page":"398","volume-title":"Proc. Parallel Problem Solving from Nature \u2014 PPSN IV","author":"P. Darwen","year":"1996","unstructured":"P. Darwen and X. Yao. Every niching method has its niche: Fitness sharing and implicit sharing compared. In Proc. Parallel Problem Solving from Nature \u2014 PPSN IV, pages 398\u2013407, New York, NY, 1996. Springer."},{"key":"53_CR3","volume-title":"Using genetic algorithms to solve NP-complete problems","author":"K. A. Jong De","year":"1989","unstructured":"K. A. De Jong and W. M. Spears. Using genetic algorithms to solve NP-complete problems. In J. D. Schaffer, editor, Proceedings of the Third International Conference on Genetic Algorithms, San Mateo, CA, 1989. Morgan Kaufman."},{"key":"53_CR4","volume-title":"An investigation of niche and species-formation in genetic function optimization","author":"K. Deb","year":"1989","unstructured":"K. Deb and D. E. Goldberg. An investigation of niche and species-formation in genetic function optimization. In J. D. Schaffer, editor, Proceedings of the Third International Conference on Genetic Algorithms, San Mateo, CA, 1989. Morgan Kaufman."},{"key":"53_CR5","doi-asserted-by":"crossref","first-page":"865","DOI":"10.1016\/0167-8655(95)00046-J","volume":"16","author":"E. S. Gelsema","year":"1995","unstructured":"E. S. Gelsema. Abductive reasoning in Bayesian belief networks using a genetic algorithm. Pattern Recognition Letters, 16:865\u2013871, 1995.","journal-title":"Pattern Recognition Letters"},{"key":"53_CR6","volume-title":"Genetic Algorithms in Search, Optimization & Machine Learning","author":"D. E. Goldberg","year":"1989","unstructured":"D. E. Goldberg. Genetic Algorithms in Search, Optimization & Machine Learning. Addison-Wesley, Reading, MA, 1989."},{"key":"53_CR7","volume-title":"Technical Report IlliGAL Report No 92005","author":"D. E. Goldberg","year":"1992","unstructured":"D. E. Goldberg, K. Deb, and J. Horn. Massive multimodality, deception, and genetic algorithms. Technical Report IlliGAL Report No 92005, University of Illinois, Urbana, 1992."},{"key":"53_CR8","unstructured":"D. E. Goldberg and J. Richardson. Genetic algorithms with sharing for multimodal function optimization. In Grefenstette [9], pages 41\u201349."},{"volume-title":"Proceedings of the Second International Conference on Genetic Algorithms","year":"1987","key":"53_CR9","unstructured":"J. J. Grefenstette, editor. Proceedings of the Second International Conference on Genetic Algorithms, Hillsdale, New Jersey, 28\u201331 July 1987. Lawrence Erlbaum Associates."},{"key":"53_CR10","volume-title":"Technical Report KSL-90-73","author":"R. Lin","year":"1990","unstructured":"R. Lin, A. Galper, and R. Shachter. Abductive inference using probabilistic networks: Randomized search techniques. Technical Report KSL-90-73, Knowledge Systems Laboratory, Stanford, November 1990."},{"key":"53_CR11","unstructured":"O. J. Mengshoel. Belief network inference in dynamic environments. In Proc. of AAAI-97, page 813, Providence, RI, 1997."},{"key":"53_CR12","unstructured":"O. J. Mengshoel, D. E. Goldberg, and D. C. Wilkins. Deceptive and other functions of unitation as Bayesian networks. In Genetic Programming 1998: Proceedings of the Third Annual Conference, Madison, WI, July 1998. To appear."},{"key":"53_CR13","first-page":"46","volume-title":"Abstraction for belief revision: Using a genetic algorithm to compute the most probable explanation","author":"O. J. Mengshoel","year":"1998","unstructured":"O. J. Mengshoel and D. C. Wilkins. Abstraction for belief revision: Using a genetic algorithm to compute the most probable explanation. In Proc. 1998 AAAI Spring Symposium on Satisficing Models, pages 46\u201353, Stanford University, CA, March 1998."},{"key":"53_CR14","volume-title":"Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference","author":"J. Pearl","year":"1988","unstructured":"J. Pearl. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann, San Mateo, California, 1988."},{"issue":"1","key":"53_CR15","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1162\/evco.1996.4.1.57","volume":"4","author":"C. Rojas-Guzman","year":"1996","unstructured":"C. Rojas-Guzman and M. A. Kramer. An evolutionary computing approach to probabilistic reasoning on Bayesian networks. Evolutionary Computation, 4(1):57\u201385, 1996.","journal-title":"Evolutionary Computation"},{"key":"53_CR16","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1016\/0004-3702(94)90072-8","volume":"68","author":"E. Shimony","year":"1994","unstructured":"E. Shimony. Finding MAPs for belief networks is NP-hard. Artificial Intelligence, 68:399\u2013410, 1994.","journal-title":"Artificial Intelligence"},{"key":"53_CR17","unstructured":"S. Srinivas and J. Breese. IDEAL: A software package for analysis of influence diagrams. In Proceedings of the Sixth Conference on Uncertainty in Artificial Intelligence, pages 212\u2013219, July 1990."},{"key":"53_CR18","unstructured":"R. L. Welch. Real time estimation of Bayesian networks. In Proceedings of the Twelfth Annual Conference on Uncertainty in Artificial Intelligence (UAI-96), pages 533\u2013544, Portland, Oregon, 1996."}],"container-title":["Lecture Notes in Computer Science","Evolutionary Programming VII"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/BFb0040806","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,2,9]],"date-time":"2019-02-09T08:24:08Z","timestamp":1549700648000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/BFb0040806"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1998]]},"ISBN":["9783540648918","9783540685159"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/bfb0040806","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[1998]]}}}