Andries P. Engelbrecht – författare

Computational Intelligence: An Introduction, Second Edition offers an in-depth exploration into the adaptive mechanisms that enable intelligent behaviour in complex and changing environments. The main focus of this text is centred on the computational modelling of biological and natural intelligent systems, encompassing swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems and evolutionary computation. Engelbrecht provides readers with a wide knowledge of Computational Intelligence (CI) paradigms and algorithms; inviting readers to implement and problem solve real-world, complex problems within the CI development framework. This implementation framework will enable readers to tackle new problems without any difficulty through a single Java class as part of the CI library.Key features of this second edition include: A tutorial, hands-on based presentation of the material.State-of-the-art coverage of the most recent developments in computational intelligence with more elaborate discussions on intelligence and artificial intelligence (AI).New discussion of Darwinian evolution versus Lamarckian evolution, also including swarm robotics, hybrid systems and artificial immune systems.A section on how to perform empirical studies; topics including statistical analysis of stochastic algorithms, and an open source library of CI algorithms.Tables, illustrations, graphs, examples, assignments, Java code implementing the algorithms, and a complete CI implementation and experimental framework.Computational Intelligence: An Introduction, Second Edition is essential reading for third and fourth year undergraduate and postgraduate students studying CI. The first edition has been prescribed by a number of overseas universities and is thus a valuable teaching tool. In addition, it will also be a useful resource for researchers in Computational Intelligence and Artificial Intelligence, as well as engineers, statisticians, operational researchers, and bioinformaticians with an interest in applying AI or CI to solve problems in their domains.Check out http://www.ci.cs.up.ac.za for examples, assignments and Java code implementing the algorithms.

Fundamentals of 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, bioinformaticians, 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 optimisation.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. Includes an accompanying website containing Java classes and implementations of the different algorithms that can be used to test PSO and ACO algorithms: http://si.cs.up.ac.zaThe interdisciplinary nature of this field will make Fundamentals of Computational Swarm Intelligence an essential resource for 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.

World Congress on Nature and Biologically InspiredComputing (NaBIC) is organized to discuss the state-of-the-art as well as toaddress various issues with respect to Nurturing Intelligent Computing TowardsAdvancement of Machine Intelligence. This Volume contains the papers presentedin the Seventh World Congress (NaBIC’15) held in Pietermaritzburg, South Africaduring December 01-03, 2015. The 39 papers presented in this Volume werecarefully reviewed and selected. The Volume would be a valuable reference toresearchers, students and practitioners in the computational intelligencefield.

These proceedings contain the papers presented at ANTS 2010, the 7th Int- national Conference on Swarm Intelligence, organized by IRIDIA, CoDE, U- versiteLibre de Bruxelles,Brussels, Belgium, during September 8-10,2010.The ANTS series started in 1998 with the First International Workshop on Ant Colony Optimization (ANTS 1998), which attracted more than 50 participants. Since then ANTS, which is held bi-annually, has gradually become an inter- tional forum for researchers in the wider ?eld of swarm intelligence. In the past (since 2004), this development has been acknowledged by the inclusion of the term"SwarmIntelligence" (nextto"AntColonyOptimization")intheconference title. This year's ANTS conference was o?cially devoted to the ?eld of swarm intelligence as a whole, without any bias towards speci?c research directions. As a result, the title of the conference was changed to "The International Conf- ence on SwarmIntelligence." This name change is already in place this year,and future ANTS conferences will continue to use the new title. Thisvolumecontainsthebestpapersselectedoutof99submissions.Ofthese, 28 were accepted as full-length papers, while 27 were accepted as short papers.This corresponds to an overall acceptance rate of 56%. Also included in this volume are 14 extended abstracts. Of the full-length papers, 15 were selected for oral presentation at the c- ference. All other contributions, including short papers and extended abstracts, werepresentedin the formof poster presentations.Following the conference,the journal Swarm Intelligence will publish extended versions of some of the best papers presented at the conference.