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Author: Dana H. Ballard Publisher: MIT Press ISBN: 9780262522588 Category : Psychology Languages : en Pages : 338
Book Description
This book provides a comprehensive introduction to the computational material that forms the underpinnings of the currently evolving set of brain models. It is now clear that the brain is unlikely to be understood without recourse to computational theories. The theme of An Introduction to Natural Computation is that ideas from diverse areas such as neuroscience, information theory, and optimization theory have recently been extended in ways that make them useful for describing the brains programs. This book provides a comprehensive introduction to the computational material that forms the underpinnings of the currently evolving set of brain models. It stresses the broad spectrum of learning models—ranging from neural network learning through reinforcement learning to genetic learning—and situates the various models in their appropriate neural context. To write about models of the brain before the brain is fully understood is a delicate matter. Very detailed models of the neural circuitry risk losing track of the task the brain is trying to solve. At the other extreme, models that represent cognitive constructs can be so abstract that they lose all relationship to neurobiology. An Introduction to Natural Computation takes the middle ground and stresses the computational task while staying near the neurobiology.
Author: Dana H. Ballard Publisher: MIT Press ISBN: 9780262522588 Category : Psychology Languages : en Pages : 338
Book Description
This book provides a comprehensive introduction to the computational material that forms the underpinnings of the currently evolving set of brain models. It is now clear that the brain is unlikely to be understood without recourse to computational theories. The theme of An Introduction to Natural Computation is that ideas from diverse areas such as neuroscience, information theory, and optimization theory have recently been extended in ways that make them useful for describing the brains programs. This book provides a comprehensive introduction to the computational material that forms the underpinnings of the currently evolving set of brain models. It stresses the broad spectrum of learning models—ranging from neural network learning through reinforcement learning to genetic learning—and situates the various models in their appropriate neural context. To write about models of the brain before the brain is fully understood is a delicate matter. Very detailed models of the neural circuitry risk losing track of the task the brain is trying to solve. At the other extreme, models that represent cognitive constructs can be so abstract that they lose all relationship to neurobiology. An Introduction to Natural Computation takes the middle ground and stresses the computational task while staying near the neurobiology.
Author: Whitman Richards Publisher: MIT Press (MA) ISBN: Category : Artificial intelligence Languages : en Pages : 584
Book Description
Designed for the MIT course, "Natural Computation, this extensive book of readings combines mathematics, artificial intelligence, computer science, experimental psychology, and neurophysiology in studying perception. Mathematics is emphasized for making perceptual inferences and the spectrum of mathematical techniques used is very broad. While the more than thirty readings focus primarily on vision, they also encompass the study of sound perception and the interpretation and application of forces including movement.Each article is a self contained example of how a perceptual problem may be tackled and solved. For example, what makes wood look like wood not like stone, sand, or grass? How can we represent three dimensional shapes when the same shape is rarely seen in exactly the same way? Each of the five sections is preceded by an introduction and the book concludes with problem sets.Whitman A. Richards is Professor in the Brain and Cognitive Science Department at MIT. A Bradford Book.
Author: Anthony Brabazon Publisher: Springer ISBN: 3662436310 Category : Computers Languages : en Pages : 554
Book Description
The field of natural computing has been the focus of a substantial research effort in recent decades. One particular strand of this research concerns the development of computational algorithms using metaphorical inspiration from systems and phenomena that occur in the natural world. These naturally inspired computing algorithms have proven to be successful problem-solvers across domains as diverse as management science, bioinformatics, finance, marketing, engineering, architecture and design. This book is a comprehensive introduction to natural computing algorithms, suitable for academic and industrial researchers and for undergraduate and graduate courses on natural computing in computer science, engineering and management science.
Author: Frank Neumann Publisher: Springer Science & Business Media ISBN: 3642165443 Category : Mathematics Languages : en Pages : 215
Book Description
Bioinspired computation methods such as evolutionary algorithms and ant colony optimization are being applied successfully to complex engineering problems and to problems from combinatorial optimization, and with this comes the requirement to more fully understand the computational complexity of these search heuristics. This is the first textbook covering the most important results achieved in this area. The authors study the computational complexity of bioinspired computation and show how runtime behavior can be analyzed in a rigorous way using some of the best-known combinatorial optimization problems -- minimum spanning trees, shortest paths, maximum matching, covering and scheduling problems. A feature of the book is the separate treatment of single- and multiobjective problems, the latter a domain where the development of the underlying theory seems to be lagging practical successes. This book will be very valuable for teaching courses on bioinspired computation and combinatorial optimization. Researchers will also benefit as the presentation of the theory covers the most important developments in the field over the last 10 years. Finally, with a focus on well-studied combinatorial optimization problems rather than toy problems, the book will also be very valuable for practitioners in this field.
Author: Xin-She Yang Publisher: Academic Press ISBN: 0128197145 Category : Technology & Engineering Languages : en Pages : 442
Book Description
Nature-inspired computation and swarm intelligence have become popular and effective tools for solving problems in optimization, computational intelligence, soft computing and data science. Recently, the literature in the field has expanded rapidly, with new algorithms and applications emerging. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is a timely reference giving a comprehensive review of relevant state-of-the-art developments in algorithms, theory and applications of nature-inspired algorithms and swarm intelligence. It reviews and documents the new developments, focusing on nature-inspired algorithms and their theoretical analysis, as well as providing a guide to their implementation. The book includes case studies of diverse real-world applications, balancing explanation of the theory with practical implementation. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is suitable for researchers and graduate students in computer science, engineering, data science, and management science, who want a comprehensive review of algorithms, theory and implementation within the fields of nature inspired computation and swarm intelligence.
Author: Giancarlo Mauri Publisher: Springer ISBN: 3642390749 Category : Computers Languages : en Pages : 275
Book Description
This book constitutes the refereed proceedings of the 12th International Conference on Unconventional Computation and Natural Computation, UCNC 2013, held in Milan, Italy, in July 2013. The 30 papers (28 full papers, 8 poster papers, and 2 invited papers) were carefully reviewed and selected from 46 submissions. The topics of the volume include: quantum, cellular, molecular, neural, DNA, membrane, and evolutionary computing; cellular automata; computation based on chaos and dynamical systems; massive parallel computation; collective intelligence; computation based on physical principles such as relativistic, optical, spatial, collision-based computing; amorphous computing; physarum computing; hypercomputation; fuzzy and rough computing; swarm intelligence; artificial immune systems; physics of computation; chemical computation; evolving hardware; the computational nature of self-assembly, developmental processes, bacterial communication, and brain processes.
Author: Irina Kostitsyna Publisher: Springer Nature ISBN: 3030879933 Category : Computers Languages : en Pages : 215
Book Description
This book constitutes the proceedings of the 19th International Conference on Unconventional Computation and Natural Computation, UCNC 2021, held in Espoo, Finland, in October 2021. The 12 full papers presented were carefully reviewed and selected from 19 submissions. The UCNC conference series covers fundamental research into computation that goes beyond the standard Turing model, including both computational models and methods inspired by nature, and the computational characteristics natural processes.
Author: Martyn Amos Publisher: Springer Science & Business Media ISBN: 3540281312 Category : Science Languages : en Pages : 180
Book Description
This book provides a broad overview of the entire field of DNA computation, tracing its history and development. It contains detailed descriptions of all major theoretical models and experimental results to date and discusses potential future developments. It concludes by outlining the challenges currently faced by researchers in the field. This book will be a useful reference for researchers and students, as well as an accessible introduction for those new to the field.
Author: Cristopher Moore Publisher: OUP Oxford ISBN: 0191620807 Category : Science Languages : en Pages : 1498
Book Description
Computational complexity is one of the most beautiful fields of modern mathematics, and it is increasingly relevant to other sciences ranging from physics to biology. But this beauty is often buried underneath layers of unnecessary formalism, and exciting recent results like interactive proofs, phase transitions, and quantum computing are usually considered too advanced for the typical student. This book bridges these gaps by explaining the deep ideas of theoretical computer science in a clear and enjoyable fashion, making them accessible to non-computer scientists and to computer scientists who finally want to appreciate their field from a new point of view. The authors start with a lucid and playful explanation of the P vs. NP problem, explaining why it is so fundamental, and so hard to resolve. They then lead the reader through the complexity of mazes and games; optimization in theory and practice; randomized algorithms, interactive proofs, and pseudorandomness; Markov chains and phase transitions; and the outer reaches of quantum computing. At every turn, they use a minimum of formalism, providing explanations that are both deep and accessible. The book is intended for graduate and undergraduate students, scientists from other areas who have long wanted to understand this subject, and experts who want to fall in love with this field all over again.
Author: Dana H. Ballard
Author: Dana H. Ballard
Author: Whitman Richards
Author: Anthony Brabazon
Author: Da-Jung Cho
Author: Frank Neumann
Author: Xin-She Yang
Author: Giancarlo Mauri
Author: Irina Kostitsyna
Author: Martyn Amos
Author: Cristopher Moore