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Full Description
Knowledge Mining Using Intelligent Agents explores the concept of knowledge discovery processes and enhances decision-making capability through the use of intelligent agents like ants, termites and honey bees. In order to provide readers with an integrated set of concepts and techniques for understanding knowledge discovery and its practical utility, this book blends two distinct disciplines — data mining and knowledge discovery process, and intelligent agents-based computing (swarm intelligence and computational intelligence). For the more advanced reader, researchers, and decision/policy-makers are given an insight into emerging technologies and their possible hybridization, which can be used for activities like dredging, capturing, distributions and the utilization of knowledge in their domain of interest (i.e. business, policy-making, etc.).By studying the behavior of swarm intelligence, this book aims to integrate the computational intelligence paradigm and intelligent distributed agents architecture to optimize various engineering problems and efficiently represent knowledge from the large gamut of data.
Contents
Part I: Theoretical Foundations of Knowledge Discovery in Databases and DM; Theoretical Foundations of Computational Intelligence; Theoretical Advances of Swarm Intelligence; Part II: Computational Intelligence for Knowledge Discovery; Genetic Algorithm for Knowledge Discovery; Genetic Programming for Knowledge Discovery; Neural Network for Knowledge discovery; Multi-objective Evolutionary Algorithms for Knowledge Discovery; Fuzzy Approach for Rule/Knowledge Mining; Part III: Swarm Intelligence for Knowledge Discovery; Particle Swarm Optimization for Knowledge Discovery; Ant Colony Optimization for Knowledge Discovery; Honey Bee Agents for Knowledge Discovery; Termites for Knowledge Discovery; Wasps for Rule/Knowledge Mining; Part IV: Hybrid Intelligent Agents Techniques for KDD and DM; Rough-Fuzzy Granule; Neuro-Fuzzy; Evolving Neural Network; Hybrid Swarm Intelligence; Part V: Applications and Future Directions; Bio-informatics; Computational Financial; Marketing/Business; Engineering Sciences.
