Challenges for Computational Intelligence

Front Cover
Springer Science & Business Media, Jun 26, 2007 - Computers - 487 pages

In the year 1900 at the International Congress of Mathematicians in Paris David Hilbert delivered what is now considered the most important talk ever given in the history of mathematics, proposing 23 major problems worth working at in the future. One hundred years later the impact of this talk is still strong: some problems have been solved, new problems have been added, but the direction once set -- identify the most important problems and focus on them
-- is still actual.

Computational Intelligence (CI) is used as a name to cover many existing branches of science, with artificial neural networks, fuzzy systems and evolutionary computation forming its core. In recent years CI has been extended by adding many other subdisciplines and it became quite obvious that this new field also requires a series of challenging problems that will give it a sense of direction. Without setting up clear goals and yardsticks to measure progress on the way many research efforts are wasted.

The book written by top experts in CI provides such clear directions and the much-needed focus on the most important and challenging research issues, showing a roadmap how to achieve ambitious goals.

 

Contents

New Millennium AI and the Convergence of History
14
The Challenges of Building Computational Cognitive
37
The Ersatz Brain Project
61
cognitive and neurocognitive processes are presented The Challenges
99
Artificial Brain and OfficeMate based on Brain Information
123
ing attention memory and reward as key elements discussing how to achieve
144
Computational Scene Analysis
163
are important for the foundations of Computational Intelligence First
192
ing about challenges facing pattern recognition and promising directions
260
KnowledgeBased Clustering in Computational Intelligence
317
Generalization in Learning from Examples
343
A Trend on Regularization and Model Selection in Statistical
364
Computational Intelligence in Mind Games
407
A Grand Challenge to
443
Noisy Chaotic Neural Networks
467
Copyright

Challenges and Opportunities by Nikola Kasabov discusses general princi
221

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