full professor in Computer Science at the University of Pretoria, South Africa
M.Sc and PhD in Computer Science from the University of Stellenbosch in 1994 and 1999 respectively
leads the Computational Intelligence Research Group(http://cirg.cs.up.ac.za/) at the University of Pretoria: swarm intelligence, evolutionary computation, neural networks, artificial immune systems, swarm robotics, image processing, bioinformatics and data & text mining
Computational Swarm Intelligence provides a comprehensive introduction to the new computational paradigm of Swarm Intelligence (SI), a field that emerged from biological research, and is now picking up momentum within the computational research community. Bio-inspired systems are becoming increasingly important research areas for computer scientists, engineers, economists, bioinformatisions, operational researchers, and many other disciplines. This book introduces the reader to the mathematical models of social insects' collective behaviour, and shows how they can be used in solving optimization problems.
Focusing on the algorithmic implementation of models of swarm behavior, this book:
examines how social network structures are used to exchange information among individuals, and how the aggregate behaviour of these individuals forms a powerful organism;
introduces a compact summary of the formal theory of optimization;
outlines paradigms with relations to SI, including genetic algorithms, evolutionary programming, evolutionary strategies, cultural algorithms and co-evolution;
looks at the choreographic movements of birds in a flock as a basis for the Particle Swarm Optimization (PSO) models, and provides an extensive treatment of different classes of PSO models
shows how the behaviour of ants can be used to implement Ant Colony Optimization (ACO) algorithms to solve real-world problems including routing optimization, structure optimization, data mining and data clustering;
considers different classes of optimization problems, including multi-objective optimization, dynamic environments, discrete and continuous search spaces, constrained optimization, and niching.
The interdisciplinary nature of this field will make Computational Swarm Intelligence an essential resource to readers with diverse backgrounds. In addition, it will be an excellent reference for computer scientists, practitioners in business or industry and researchers involved in the analysis, design and simulation of multibody systems. Advanced undergraduates and graduate students in artificial intelligence, collective intelligence and engineering, will also find this book an invaluable tool.
Making Sense of Data: a practical guide to exploratory data analysis and data mining
subscription 연장하려 하였으나, 목록에서 사라졌다. 찾아보았으나, 링크들은 여기 저기에 남아 있는데, 정작 목표 페이지는 없어졌다. Chicago Journal of Theoretical Computer Science, CJTCS. ISSN 1073-0486. 이런?!
