Journal ArticleDOI
Fundamentals of natural computing: an overview
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This paper provides an overview of the fundamentals of natural computing, particularly the fields listed above, emphasizing the biological motivation, some design principles, their scope of applications, current research trends and open problems.About:
This article is published in Physics of Life Reviews.The article was published on 2007-03-01. It has received 278 citations till now. The article focuses on the topics: Natural computing & Bio-inspired computing.read more
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The computational brain: Patricia S. Churchland and Terrence J. Sejnowski (MIT Press, Cambridge, MA, 1992); xi, 544 pages, $39.95
TL;DR: The Computational Brain this paper provides a broad overview of neuroscience and computational theory, followed by a study of some of the most recent and sophisticated modeling work in the context of relevant neurobiological research.
Plenary lecture VIII: toward physics of the mind: concepts, emotions, consciousness, and symbols
TL;DR: In this paper, a scheme for reducing combinatorial complexity often encountered in the past attempts at designing "intelligent systems", and briefly discuss engineering applications (data mining, fusion, financial predictions, Internet search engine, etc.).
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Recent advances in engineering design optimisation: Challenges and future trends
TL;DR: This paper identifies recent approaches to automating the manual optimisation process and the challenges that it presents to the engineering community.
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Neural networks
Alberto Prieto,Beatriz Prieto,Eva M. Ortigosa,Eduardo Ros,Francisco J. Pelayo,Julio Ortega,Ignacio Rojas +6 more
TL;DR: The development and evolution of different topics related to neural networks is described showing that the field has acquired maturity and consolidation, proven by its competitiveness in solving real-world problems.
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Nature Inspired Computing: An Overview and Some Future Directions
Nazmul Siddique,Hojjat Adeli +1 more
TL;DR: An overview of significant advances made in the emerging field of nature-inspired computing with a focus on the physics- and biology-based approaches and algorithms is presented.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Book
The Nature of Statistical Learning Theory
TL;DR: Setting of the learning problem consistency of learning processes bounds on the rate of convergence ofLearning processes controlling the generalization ability of learning process constructing learning algorithms what is important in learning theory?
Book
Computers and Intractability: A Guide to the Theory of NP-Completeness
TL;DR: The second edition of a quarterly column as discussed by the authors provides a continuing update to the list of problems (NP-complete and harder) presented by M. R. Garey and myself in our book "Computers and Intractability: A Guide to the Theory of NP-Completeness,” W. H. Freeman & Co., San Francisco, 1979.
Book
Reinforcement Learning: An Introduction
TL;DR: This book provides a clear and simple account of the key ideas and algorithms of reinforcement learning, which ranges from the history of the field's intellectual foundations to the most recent developments and applications.