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.

    This article is arguably the most influential and widely read article in the philosophy of artificial intelligence. Indeed, most of the debate in the philosophy of artificial intelligence over the last fifty years concerns issues that were raised and discussed by Turing. Turing's genius was not only in developing the theory of computability but also in understanding the impact, both practical and philosophical, that computing machinery would have. Turing believed that computers, if properly designed and educated, could exhibit intelligent behavior, even behavior that would be indistinguishable from human intelligent behavior. His vision of the possibility of machine intelligence has been highly inspiring and extremely controversial. In this classic article Turing presented his well known imitation game and predicted that about the year 2000 "an average interrogator will not have more than 70 per cent chance of making the right identification after five minutes of questioning" in the imitation game. Based on the results of the Loebner 2000 contest and the accomplishments in the field of AI, as impressive as they are, Turing's prediction remains unfulfilled.