Intelligent Machines: Myths and RealitiesClarence W. de Silva What is intelligence? Are truly intelligent machines a practical reality? If so, can they work in harmony with human beings and improve the quality of our lives? How are they designed, built, and controlled? The fact is that machines with brains are no longer the stuff of science fiction. Research focused on developing smarter, more flexible machines and new applications continues at a remarkable pace, yet for many people-even engineers-these and other questions linger. Intelligent Machines: Myths and Realities explores the technological, industrial, economic, social, and research issues related to intelligent machines. Nine chapters-authored by highly distinguished international authorities-take you from the fundamentals and general aspects of intelligent machines through current techniques and research, and finally to their practical aspects and applications. Written for both technical and nontechnical readers, Intelligent Machines presents complex issues in simple, qualitative terms, yet discusses important theoretical aspects, industrial applications, and design issues where they are appropriate. The result is an intriguing exploration of this revolutionary technology, its design, uses, limitations, and future prospects. Features |
Contents
What Makes a Machine Intelligent? | 1 |
Information Knowledge and Machines | 43 |
Machines and the Elusive Wisdom | 77 |
Research Advances in Intelligent Machines | 111 |
Soft Computing Tools for Intelligent Machines | 139 |
Soft Computing Control of Complex Systems | 185 |
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ability adaptive agents applications approach artificial intelligence artificial neural network Automation autonomous backpropagation behavior capabilities chapter chine chromosomes complex concepts context control system crisp crossover decision dynamic encoding Engineering enhancement environment Equation example expert system feature Figure fuzzy control fuzzy logic fuzzy rules fuzzy set Fuzzy Systems genetic algorithms genotype given holons Hopfield network human human-machine IEEE implemented industrial inference input instantiated integration intelligent control intelligent machines intelligent systems interaction knowledge base knowledge system knowledge-based learning algorithm machine intelligence manufacturing MdDb mechanism membership functions method mobile robots mutation neural networks neuro-fuzzy neurons nodes nonlinear objective knowledge operation optimization parameters pattern performance population prediction problem Proc production represent representation ROC curve selection sense sensor fusion soft computing solution space structure task techniques theory tion tracking error University values variables vector