Includes bibliographical references and index.

Machine generated contents note: Part One: General Heuristics -- Chapter 1: From Evolution to Immune to Swarm to? -- A Simple Introduction to Modern Heuristics1 -- Hussein A. Abbass, University of New South Wales, Australia -- Chapter 2: Approximating Proximityfor Fast andRobust -- Distance-Based Clustering22 -- Vladimir Estivill-Castro, University of Newcastle, Australia -- Michael Houle, University of Sydney, Australia -- Part Two: Evolutionary Algorithms -- Chapter3: On the Use of Evolutionary Algorithmsin Data Mining48 -- Erick Cantu-Paz, Lawrence Livermore National Laboratory, USA -- Chandrika Kamath, Lawrence Livermore National Laboratory, USA -- Chapter 4: The discovery of interesting nuggets using heuristic techniques72 -- Beatriz de la Iglesia, University of East Anglia, UK -- Victor J. Rayward-Smith, University of East Anglia, UK -- Chapter5: Estimation of Distribution Algorithms forFeature Subset -- Selection in Large Dimensionality Domains97 -- Ifiaki Inza, University of the Basque Country, Spain -- Pedro Larranaga, University of the Basque Country, Spain -- Basilio Sierra, University of the Basque Country, Spain -- Chapter 6: Towards the Cross-Fertilization of Multiple Heuristics: -- Evolving Teams of Local Bayesian Learners117 -- Jorge Muruzdbal, Universidad Rey Juan Carlos, Spain -- Chapter 7: Evolution of SpatialData Templates for Object Classification143 -- Neil Dunstan, University of New England, Australia -- Michael de Raadt, University of Southern Queensland, Australia -- Part Three: Genetic Programming -- Chapter 8: Genetic Programming as a Data-Mining Tool157 -- Peter W.H. Smith, City University, UK -- Chapter 9: A Building BlockApproach to Genetic Programming -- for Rule Discovery174 -- A.P. Engelbrecht, University of Pretoria, South Africa -- Sonja Rouwhorst, Vrije Universiteit Amsterdam, The Netherlands -- L. Schoeman, University of Pretoria, South Africa -- Part Four: Ant Colony Optimization and Immune Systems -- Chapter 10: An Ant Colony Algorithm for Classification Rule Discovery 191 -- Rafael S. Parpinelli, Centro Federal de Educacao Tecnologica do Parana, Brazil -- Heitor S. Lopes, Centro Federal de Educacao Tecnologica do Parana, Brazil -- Alex A. Freitas, Pontificia Universidade Catolica do Parana, Brazil -- Chapter 11: ArtificialImmune Systems: Using the Immune System -- as Inspiration forDataMining209 -- Jon Timmis, University of Kent at Canterbury, UK -- Thomas Knight, University of Kent at Canterbury, UK -- Chapter 12: aiNet: An Artificial Immune Network for Data Analysis231 -- Leandro Nunes de Castro, State University of Campinas, Brazil -- Fernando J. Von Zuben, State University of Campinas, Brazil -- Part Five: Parallel Data Mining -- Chapter 13: Parallel Data Mining261 -- David Taniar, Monash University, Australia -- J. Wenny Rahayu, La Trobe University, Australia.