{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,5]],"date-time":"2024-09-05T06:39:23Z","timestamp":1725518363046},"publisher-location":"Berlin, Heidelberg","reference-count":35,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783540850670"},{"type":"electronic","value":"9783540850687"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"DOI":"10.1007\/978-3-540-85068-7_5","type":"book-chapter","created":{"date-parts":[[2008,9,10]],"date-time":"2008-09-10T02:33:14Z","timestamp":1221013994000},"page":"87-107","source":"Crossref","is-referenced-by-count":1,"title":["Linkage Learning Accuracy in the Bayesian Optimization Algorithm"],"prefix":"10.1007","author":[{"given":"Claudio F.","family":"Lima","sequence":"first","affiliation":[]},{"given":"Martin","family":"Pelikan","sequence":"additional","affiliation":[]},{"given":"David E.","family":"Goldberg","sequence":"additional","affiliation":[]},{"given":"Fernando G.","family":"Lobo","sequence":"additional","affiliation":[]},{"given":"Kumara","family":"Sastry","sequence":"additional","affiliation":[]},{"given":"Mark","family":"Hauschild","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"key":"5_CR1","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4613-1997-9","volume-title":"A connectionist machine for genetic hill climbing","author":"D.H. Ackley","year":"1987","unstructured":"Ackley, D.H.: A connectionist machine for genetic hill climbing. Kluwer Academic, Boston (1987)"},{"issue":"4","key":"5_CR2","first-page":"311","volume":"4","author":"T. Blickle","year":"1997","unstructured":"Blickle, T., Thiele, L.: A comparison of selection schemes used in genetic algorithms. Evolutionary Computation\u00a04(4), 311\u2013347 (1997)","journal-title":"Evolutionary Computation"},{"unstructured":"Brindle, A.: Genetic Algorithms for Function Optimization. PhD thesis, University of Alberta, Edmonton, Canada. Unpublished doctoral dissertation (1981)","key":"5_CR3"},{"unstructured":"Chickering, D.M., Heckerman, D., Meek, C.: A Bayesian approach to learning Bayesian networks with local structure. Technical Report MSR-TR-97-07, Microsoft Research, Redmond, WA (1997)","key":"5_CR4"},{"key":"5_CR5","first-page":"309","volume":"9","author":"G.F. Cooper","year":"1992","unstructured":"Cooper, G.F., Herskovits, E.H.: A Bayesian method for the induction of probabilistic networks from data. Machine Learning\u00a09, 309\u2013347 (1992)","journal-title":"Machine Learning"},{"key":"5_CR6","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"998","DOI":"10.1007\/11844297_101","volume-title":"Parallel Problem Solving from Nature - PPSN IX","author":"E.S. Correa","year":"2006","unstructured":"Correa, E.S., Shapiro, J.L.: Model complexity vs. performance in the bayesian optimization algorithm. In: Runarsson, T.P., Beyer, H.-G., Burke, E.K., Merelo-Guerv\u00f3s, J.J., Whitley, L.D., Yao, X. (eds.) PPSN 2006. LNCS, vol.\u00a04193, pp. 998\u20131007. Springer, Heidelberg (2006)"},{"key":"5_CR7","first-page":"93","volume":"2","author":"K. Deb","year":"1993","unstructured":"Deb, K., Goldberg, D.E.: Analyzing deception in trap functions. Foundations of Genetic Algorithms\u00a02, 93\u2013108 (1993)","journal-title":"Foundations of Genetic Algorithms"},{"key":"5_CR8","doi-asserted-by":"publisher","first-page":"1051","DOI":"10.1109\/CEC.2007.4424586","volume-title":"Proceedings of the IEEE Congress on Evolutionary Computation","author":"C. Echegoyen","year":"2007","unstructured":"Echegoyen, C., Lozano, J.A., Santana, R., Larra\u00f1aga, P.: Exact bayesian network learning in estimation of distribution algorithms. In: Proceedings of the IEEE Congress on Evolutionary Computation, pp. 1051\u20131058. IEEE Press, Los Alamitos (2007)"},{"doi-asserted-by":"crossref","unstructured":"Friedman, N., Goldszmidt, M.: Learning bayesian networks with local structure. Graphical Models, 421\u2013459 (1999)","key":"5_CR9","DOI":"10.1007\/978-94-011-5014-9_15"},{"key":"5_CR10","volume-title":"The Design of Innovation - Lessons from and for Competent Genetic Algorithms","author":"D.E. Goldberg","year":"2002","unstructured":"Goldberg, D.E.: The Design of Innovation - Lessons from and for Competent Genetic Algorithms. Kluwer Academic Publishers, Norwell (2002)"},{"issue":"5","key":"5_CR11","first-page":"493","volume":"3","author":"D.E. Goldberg","year":"1989","unstructured":"Goldberg, D.E., Korb, B., Deb, K.: Messy genetic algorithms: Motivation, analysis, and first results. Complex Systems\u00a03(5), 493\u2013530 (1989)","journal-title":"Complex Systems"},{"unstructured":"Harik, G.R.: Finding multimodal solutions using restricted tournament selection. In: Proceedings of the Sixth International Conference on Genetic Algorithms, pp. 24\u201331 (1995)","key":"5_CR12"},{"doi-asserted-by":"crossref","unstructured":"Hauschild, M., Pelikan, M., Lima, C.F., Sastry, K.: Analyzing probabilistic models in hierarchical BOA on traps and spin glasses. MEDAL Report No. 2007001, University of Missouri at St. Louis, St. Louis, MO (2007)","key":"5_CR13","DOI":"10.1145\/1276958.1277070"},{"doi-asserted-by":"crossref","unstructured":"Heckerman, D., Geiger, D., Chickering, D.M.: Learning Bayesian networks: The combination of knowledge and statistical data. Technical Report MSR-TR-94-09, Microsoft Research, Redmond, WA (1994)","key":"5_CR14","DOI":"10.1016\/B978-1-55860-332-5.50042-0"},{"key":"5_CR15","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4615-1539-5","volume-title":"Estimation of distribution algorithms: a new tool for Evolutionary Computation","author":"P. Larra\u00f1aga","year":"2002","unstructured":"Larra\u00f1aga, P., Lozano, J.A.: Estimation of distribution algorithms: a new tool for Evolutionary Computation. Kluwer Academic Publishers, Boston (2002)"},{"doi-asserted-by":"crossref","unstructured":"Lima, C.F., Lobo, F.G., Pelikan, M.: From mating-pool distributions to model overfitting. In: Accepted for the ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO 2008) (2008)","key":"5_CR16","DOI":"10.1145\/1389095.1389174"},{"key":"5_CR17","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"232","DOI":"10.1007\/11844297_24","volume-title":"Parallel Problem Solving from Nature - PPSN IX","author":"C.F. Lima","year":"2006","unstructured":"Lima, C.F., Pelikan, M., Sastry, K., Butz, M., Goldberg, D.E., Lobo, F.G.: Substructural neighborhoods for local search in the Bayesian optimization algorithm. In: Runarsson, T.P., Beyer, H.-G., Burke, E.K., Merelo-Guerv\u00f3s, J.J., Whitley, L.D., Yao, X. (eds.) PPSN 2006. LNCS, vol.\u00a04193, pp. 232\u2013241. Springer, Heidelberg (2006)"},{"key":"5_CR18","doi-asserted-by":"publisher","first-page":"735","DOI":"10.1145\/1068009.1068131","volume-title":"Proceedings of the ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO 2005)","author":"C.F. Lima","year":"2005","unstructured":"Lima, C.F., Sastry, K., Goldberg, D.E., Lobo, F.G.: Combining competent crossover and mutation operators: a probabilistic model building approach. In: Beyer, H., et al. (eds.) Proceedings of the ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO 2005), pp. 735\u2013742. ACM Press, New York (2005)"},{"issue":"1","key":"5_CR19","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1162\/evco.1993.1.1.25","volume":"1","author":"H. M\u00fchlenbein","year":"1993","unstructured":"M\u00fchlenbein, H., Schlierkamp-Voosen, D.: Predictive models for the breeder genetic algorithm: I. Continuous parameter optimization. Evolutionary Computation\u00a01(1), 25\u201349 (1993)","journal-title":"Evolutionary Computation"},{"key":"5_CR20","volume-title":"Probabilistic reasoning in intelligent systems: Networks of plausible inference","author":"J. Pearl","year":"1988","unstructured":"Pearl, J.: Probabilistic reasoning in intelligent systems: Networks of plausible inference. Morgan Kaufmann, San Mateo (1988)"},{"key":"5_CR21","doi-asserted-by":"crossref","DOI":"10.1007\/b10910","volume-title":"Hierarchical Bayesian Optimization Algorithm: Toward a New Generation of Evolutionary Algorithms","author":"M. Pelikan","year":"2005","unstructured":"Pelikan, M.: Hierarchical Bayesian Optimization Algorithm: Toward a New Generation of Evolutionary Algorithms. Springer, Heidelberg (2005)"},{"key":"5_CR22","first-page":"511","volume-title":"Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2001)","author":"M. Pelikan","year":"2001","unstructured":"Pelikan, M., Goldberg, D.E.: Escaping hierarchical traps with competent genetic algorithms. In: Spector, L., et al. (eds.) Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2001), pp. 511\u2013518. Morgan Kaufmann, San Francisco (2001)"},{"key":"5_CR23","first-page":"525","volume-title":"Proceedings of the Genetic and Evolutionary Computation Conference GECCO 1999","author":"M. Pelikan","year":"1999","unstructured":"Pelikan, M., Goldberg, D.E., Cantu-Paz, E.: BOA: The Bayesian Optimization Algorithm. In: Banzhaf, W., et al. (eds.) Proceedings of the Genetic and Evolutionary Computation Conference GECCO 1999, pp. 525\u2013532. Morgan Kaufmann, San Francisco (1999)"},{"issue":"1","key":"5_CR24","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1013500812258","volume":"21","author":"M. Pelikan","year":"2002","unstructured":"Pelikan, M., Goldberg, D.E., Lobo, F.: A survey of optimization by building and using probabilistic models. Computational Optimization and Applications\u00a021(1), 5\u201320 (2002)","journal-title":"Computational Optimization and Applications"},{"key":"5_CR25","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1007\/978-3-540-24855-2_5","volume-title":"Genetic and Evolutionary Computation \u2013 GECCO 2004","author":"M. Pelikan","year":"2004","unstructured":"Pelikan, M., Sastry, K.: Fitness inheritance in the bayesian optimization algorithm. In: Deb, K., et al. (eds.) GECCO 2004. LNCS, vol.\u00a03103, pp. 48\u201359. Springer, Heidelberg (2004)"},{"key":"5_CR26","doi-asserted-by":"publisher","first-page":"1418","DOI":"10.1109\/CEC.2005.1554856","volume-title":"Proceedings of the IEEE Congress on Evolutionary Computation","author":"R. Santana","year":"2005","unstructured":"Santana, R., Larra\u00f1aga, P., Lozano, J.A.: Interactions and dependencies in estimation of distribution algorithms. In: Proceedings of the IEEE Congress on Evolutionary Computation, pp. 1418\u20131425. IEEE Press, Los Alamitos (2005)"},{"unstructured":"Sastry, K.: Evaluation-relaxation schemes for genetic and evolutionary algorithms. Master\u2019s thesis, University of Illinois at Urbana-Champaign, Urbana, IL (2001)","key":"5_CR27"},{"key":"5_CR28","volume-title":"Proceedings of the ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO 2005)","author":"K. Sastry","year":"2005","unstructured":"Sastry, K., Abbass, H.A., Goldberg, D.E., Johnson, D.D.: Sub-structural niching in estimation distribution algorithms. In: Beyer, H., et al. (eds.) Proceedings of the ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO 2005). ACM Press, New York (2005)"},{"key":"5_CR29","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1007\/978-3-540-24855-2_11","volume-title":"Genetic and Evolutionary Computation \u2013 GECCO 2004","author":"K. Sastry","year":"2004","unstructured":"Sastry, K., Goldberg, D.E.: Designing competent mutation operators via probabilistic model building of neighborhoods. In: Deb, K., et al. (eds.) GECCO 2004. LNCS, vol.\u00a03103, pp. 114\u2013125. Springer, Heidelberg (2004)"},{"key":"5_CR30","doi-asserted-by":"publisher","first-page":"419","DOI":"10.1145\/1143997.1144074","volume-title":"Proceedings of the ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO 2006)","author":"K. Sastry","year":"2006","unstructured":"Sastry, K., Lima, C.F., Goldberg, D.E.: Evaluation relaxation using substructural information and linear estimation. In: Keijzer, M., et al. (eds.) Proceedings of the ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO 2006), pp. 419\u2013426. ACM Press, New York (2006)"},{"doi-asserted-by":"crossref","unstructured":"Sastry, K., Pelikan, M., Goldberg, D.E.: Efficiency enhancement of genetic algorithms via building-block-wise fitness estimation. In: Proceedings of the IEEE International Conference on Evolutionary Computation, pp. 720\u2013727 (2004)","key":"5_CR31","DOI":"10.1109\/CEC.2004.1330930"},{"key":"5_CR32","first-page":"38","volume-title":"Proceedings of the Fifth International Conference on Genetic Algorithms","author":"D. Thierens","year":"1993","unstructured":"Thierens, D., Goldberg, D.E.: Mixing in genetic algorithms. In: Forrest, S. (ed.) Proceedings of the Fifth International Conference on Genetic Algorithms, pp. 38\u201345. Morgan Kaufmann, San Mateo (1993)"},{"key":"5_CR33","doi-asserted-by":"publisher","first-page":"433","DOI":"10.1145\/1143997.1144078","volume-title":"Proceedings of the ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO 2006)","author":"H. Wu","year":"2006","unstructured":"Wu, H., Shapiro, J.L.: Does overfitting affect performance in estimation of distribution algorithms. In: Keijzer, M., others (eds.) Proceedings of the ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO 2006), pp. 433\u2013434. ACM Press, New York (2006)"},{"key":"5_CR34","series-title":"Lecture Notes in Computer Science","first-page":"355","volume-title":"Genetic and Evolutionary Computation \u2013 GECCO 2004","author":"T.-L. Yu","year":"2004","unstructured":"Yu, T.-L., Goldberg, D.E.: Dependency structure matrix analysis: Offline utility of the dependency structure matrix genetic algorithm. In: Deb, K.,et al. (eds.) GECCO 2004. LNCS, vol.\u00a03103, pp. 355\u2013366. Springer, Heidelberg (2004)"},{"key":"5_CR35","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1007\/978-3-540-69432-8_10","volume-title":"Parameter Setting in Evolutionary Algorithms","author":"T.-L. Yu","year":"2007","unstructured":"Yu, T.-L., Sastry, K., Goldberg, D.E.: Population size to go: Online adaptation using noise and substructural measurements. In: Lobo, F.G., et al. (eds.) Parameter Setting in Evolutionary Algorithms, pp. 205\u2013224. Springer, Heidelberg (2007)"}],"container-title":["Studies in Computational Intelligence","Linkage in Evolutionary Computation"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-540-85068-7_5.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,11,24]],"date-time":"2020-11-24T02:21:29Z","timestamp":1606184489000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-540-85068-7_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[null]]},"ISBN":["9783540850670","9783540850687"],"references-count":35,"URL":"https:\/\/doi.org\/10.1007\/978-3-540-85068-7_5","relation":{},"ISSN":["1860-949X","1860-9503"],"issn-type":[{"type":"print","value":"1860-949X"},{"type":"electronic","value":"1860-9503"}],"subject":[]}}