IEEE Press - Wiley, 2003, 282 pages, ISBN: 0-471-27454-2
This book provides an expanded, peer-reviewed record of many of these outstanding presentations, which were both a summary of current technology as well as a look to the future and a forecast of what problems and discoveries await us in computational intelligence.
The papers presented here not only identify diverse aspects of groundbreaking research in self-organizing systems, situation awareness, human-machine interaction, gleaning insight from data, automatic control, supplementing human intelligence' and many other areas, they also indicate the challenges that we face and place the efforts of the computational intelligence community in perspective, without hype or undue pessimism. The result is a balanced, fair assessment of where our community stands now, still at the dawn of the new millennium, and a map to guide future efforts. Moreover, some of the results presented in this book represent novel contributions to the field of computational intelligence, and thus the book serves both as primary reference literature and as a tutorial and survey.
Three generations of coevolutionary robotics
Beyond 2001: the linguistic spatial odyssey
Computing machinery and intelligence amplification
Visualizing complexity in the brain
Emerging technologies: onr's need for intelligent computation in underwater sensors
Beyond volterra and wiener: optimal modeling of nonlinear dynamical systems in a neural space for applications in computational intelligence
Techniques for extracting classification and regression rules from artificial neural networks
Neural networks for control: research opportunities and recent developments
Intelligent learning robotic systems using computational intelligence
Computational intelligence in logistics
Two new convergence results for alternating optimization
Constructive design of a discrete-time fuzzy controller based on Piecewise-Lyapunov functions
Evolutionary computation and cognitive science
Evolvable hardware and its applications
Humanized computational intelligence with interactive evolutionary computation
Unsupervised learning by artificial neural networks
Collective intelligence
Backpropagation: general principles and issues for biology