Hussein A. AbbassVladimir Estivill-Castro and Michael HouleErick Cantu-Paz and Chandrika KamathBeatriz de la Iglesia and Victor J. Rayward-SmithInaki Inza and Pedro Larranaga and Basilio SierraJorge MuruzabalNeil Dunstan and Michael de RaadtPeter W.H. SmithA.P. Engelbrecht and Sonja Rouwhorst and L. SchoemanRafael S. Parpinelli and Heitor S. Lopes and Alex A. FreitasJon Timmis and Thomas KnightLeandro Nunes de Castro and Fernando J. Von ZubenDavid Taniar and J. Wenny Rahayu

Preface	p. i
Part 1 General Heuristics
Chapter 1 From Evolution to Immune to Swarm to...? A Simple Introduction to Modern Heuristics	p. 1
Chapter 2 Approximating Proximity for Fast and Robust Distance-Based Clustering	p. 22
Part 2 Evolutionary Algorithms
Chapter 3 On the Use of Evolutionary Algorithms in Data Mining	p. 48
Chapter 4 The discovery of interesting nuggets using heuristic techniques	p. 72
Chapter 5 Estimation of Distribution Algorithms for Feature Subset Selection in Large Dimensionality Domains	p. 97
Chapter 6 Towards the Cross-Fertilization of Multiple Heuristics: Evolving Teams of Local Bayesian Learners	p. 117
Chapter 7 Evolution of Spatial Data Templates for Object Classification	p. 143
Part 3 Genetic Programming
Chapter 8 Genetic Programming as a Data-Mining Tool	p. 157
Chapter 9 A Building Block Approach to Genetic Programming for Rule Discovery	p. 174
Part 4 Ant Colony Optimization and Immune Systems
Chapter 10 An Ant Colony Algorithm for Classification Rule Discovery	p. 191
Chapter 11 Artificial Immune Systems: Using the Immune System as Inspiration for Data Mining	p. 209
Chapter 12 aiNet: An Artificial Immune Network for Data Analysis	p. 231
Part 5 Parallel Data Mining
Chapter 13 Parallel Data Mining	p. 261
About the Authors	p. 290
Index	p. 297