Unified computational intelligence for complex systems [electronic resource]
- 作者: Seiffertt, John.
- 其他作者:
- 出版: Berlin, Heidelberg : Springer-Verlag Berlin Heidelberg
- 叢書名: Adaptation, learning and optimization,v.6
- 主題: System design , Computational intelligence , Computational complexity , Engineering , Computational intelligence , Complexity. , Artificial Intelligence (incl. Robotics) , Game Theory/Mathematical Methods. , Statistical Physics, Dynamical Systems and Complexity.
- ISBN: 9783642031809 (electronic bk.) 、 9783642031793 (paper)
- FIND@SFXID: CGU
- 資料類型: 電子書
-
讀者標籤:
- 系統號: 005063180 | 機讀編目格式
館藏資訊
Computational intelligence encompasses a wide variety of techniques that allow computation to learn, to adapt, and to seek. That is, they may be designed to learn information without explicit programming regarding the nature of the content to be retained, they may be imbued with the functionality to adapt to maintain their course within a complex and unpredictably changing environment, and they may help us seek out truths about our own dynamics and lives through their inclusion in complex system modeling. These capabilities place our ability to compute in a category apart from our ability to erect suspension bridges, although both are products of technological advancement and reflect an increased understanding of our world. In this book, we show how to unify aspects of learning and adaptation within the computational intelligence framework. While a number of algorithms exist that fall under the umbrella of computational intelligence, with new ones added every year, all of them focus on the capabilities of learning, adapting, and helping us seek. So, the term unified computational intelligence relates not to the individual algorithms but to the underlying goals driving them. This book focuses on the computational intelligence areas of neural networks and dynamic programming, showing how to unify aspects of these areas to create new, more powerful, computational intelligence architectures to apply to new problem domains.