Computational Intelligence
An Introduction
2. Edition October 2007
628 Pages, Hardcover
Practical Approach Book
Short Description
Computational Intelligence: An Introduction, Second Edition focuses on computational modeling of biological and natural intelligent systems in order to develop nature-inspired artificially intelligent systems. This second edition provides a more detailed and equal treatment of paradigms, and includes most recent advances in CI, namely artificial immune systems, hybrid systems, and a section on how to perform empirical studies.
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 www.http://ci.cs.up.ac.za for examples, assignments and Java code implementing the algorithms.
Tables.
Algorithms.
Preface.
Part I INTRODUCTION.
1 Introduction to Computational Intelligence.
Part II ARTIFICIAL NEURAL NETWORKS.
2 The Artificial Neuron.
3 Supervised Learning Neural Networks.
4 Unsupervised Learning Neural Networks.
5 Radial Basis Function Networks.
6 Reinforcement Learning.
7 Performance Issues (Supervised Learning).
Part III EVOLUTIONARY COMPUTATION.
8 Introduction to Evolutionary Computation.
9 Genetic Algorithms.
10 Genetic Programming.
11 Evolutionary Programming.
12 Evolution Strategies.
13 Differential Evolution.
14 Cultural Algorithms.
15 Coevolution.
Part IV COMPUTATIONAL SWARM INTELLIGENCE.
16 Particle Swarm Optimization.
17 Ant Algorithms.
Part V ARTIFICIAL IMMUNE SYSTEMS.
18 Natural Immune System.
19 Artificial Immune Models.
Part VI FUZZY SYSTEMS.
20 Fuzzy Sets.
21 Fuzzy Logic and Reasoning.
22 Fuzzy Controllers.
23 Rough Sets.
References.
A Optimization Theory.
Index.
