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Author: David E. Rumelhart
Publisher:
ISBN:
Category : Cognition
Languages : en
Pages : 0
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Book Description
What makes people smarter than computers? These volumes by a pioneering neurocomputing group suggest that the answer lies in the massively parallel architecture of the human mind. They describe a new theory of cognition called connectionism that is challenging the idea of symbolic computation that has traditionally been at the center of debate in theoretical discussions about the mind. The authors' theory assumes the mind is composed of a great number of elementary units connected in a neural network. Mental processes are interactions between these units which excite and inhibit each other in parallel rather than sequential operations. In this context, knowledge can no longer be thought of as stored in localized structures; instead, it consists of the connections between pairs of units that are distributed throughout the network. Volume 1 lays the foundations of this exciting theory of parallel distributed processing, while Volume 2 applies it to a number of specific issues in cognitive science and neuroscience, with chapters describing models of aspects of perception, memory, language, and thought.
Author: David E. Rumelhart
Publisher:
ISBN:
Category : Cognition
Languages : en
Pages : 0
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Book Description
What makes people smarter than computers? These volumes by a pioneering neurocomputing group suggest that the answer lies in the massively parallel architecture of the human mind. They describe a new theory of cognition called connectionism that is challenging the idea of symbolic computation that has traditionally been at the center of debate in theoretical discussions about the mind. The authors' theory assumes the mind is composed of a great number of elementary units connected in a neural network. Mental processes are interactions between these units which excite and inhibit each other in parallel rather than sequential operations. In this context, knowledge can no longer be thought of as stored in localized structures; instead, it consists of the connections between pairs of units that are distributed throughout the network. Volume 1 lays the foundations of this exciting theory of parallel distributed processing, while Volume 2 applies it to a number of specific issues in cognitive science and neuroscience, with chapters describing models of aspects of perception, memory, language, and thought.
Author: Timothy T. Rogers
Publisher: MIT Press
ISBN: 9780262182393
Category : Computers
Languages : en
Pages : 446
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Book Description
A mechanistic theory of the representation and use of semantic knowledge that uses distributed connectionist networks as a starting point for a psychological theory of semantic cognition.
Author: Michael Alexander
Publisher: CRC Press
ISBN: 1420064878
Category : Mathematics
Languages : en
Pages : 440
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Book Description
Collects the Latest Research Involving the Application of Process Algebra to ComputingExploring state-of-the-art applications, Process Algebra for Parallel and Distributed Processing shows how one formal method of reasoning-process algebra-has become a powerful tool for solving design and implementation challenges of concurrent systems. Parallel Pr
Author: Andy Clark
Publisher: MIT Press (MA)
ISBN:
Category : Computers
Languages : en
Pages : 250
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Book Description
A guide to parallel distributed processing, an emerging paradigm which is transforming the field of cognitive science. It explains and explores the biological basis of PDP, its psychological importance, and its philosophical relevance - particularly to the study of folk-psychology.
Author: Kai Hwang
Publisher: Morgan Kaufmann
ISBN: 0128002042
Category : Computers
Languages : en
Pages : 671
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Book Description
Distributed and Cloud Computing: From Parallel Processing to the Internet of Things offers complete coverage of modern distributed computing technology including clusters, the grid, service-oriented architecture, massively parallel processors, peer-to-peer networking, and cloud computing. It is the first modern, up-to-date distributed systems textbook; it explains how to create high-performance, scalable, reliable systems, exposing the design principles, architecture, and innovative applications of parallel, distributed, and cloud computing systems. Topics covered by this book include: facilitating management, debugging, migration, and disaster recovery through virtualization; clustered systems for research or ecommerce applications; designing systems as web services; and social networking systems using peer-to-peer computing. The principles of cloud computing are discussed using examples from open-source and commercial applications, along with case studies from the leading distributed computing vendors such as Amazon, Microsoft, and Google. Each chapter includes exercises and further reading, with lecture slides and more available online. This book will be ideal for students taking a distributed systems or distributed computing class, as well as for professional system designers and engineers looking for a reference to the latest distributed technologies including cloud, P2P and grid computing. - Complete coverage of modern distributed computing technology including clusters, the grid, service-oriented architecture, massively parallel processors, peer-to-peer networking, and cloud computing - Includes case studies from the leading distributed computing vendors: Amazon, Microsoft, Google, and more - Explains how to use virtualization to facilitate management, debugging, migration, and disaster recovery - Designed for undergraduate or graduate students taking a distributed systems course—each chapter includes exercises and further reading, with lecture slides and more available online
Author: J.W. Donahoe
Publisher: Elsevier
ISBN: 0080537367
Category : Computers
Languages : en
Pages : 601
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Book Description
This internationally authored volume presents major findings, concepts, and methods of behavioral neuroscience coordinated with their simulation via neural networks. A central theme is that biobehaviorally constrained simulations provide a rigorous means to explore the implications of relatively simple processes for the understanding of cognition (complex behavior). Neural networks are held to serve the same function for behavioral neuroscience as population genetics for evolutionary science. The volume is divided into six sections, each of which includes both experimental and simulation research: (1) neurodevelopment and genetic algorithms, (2) synaptic plasticity (LTP), (3) sensory/hippocampal systems, (4) motor systems, (5) plasticity in large neural systems (reinforcement learning), and (6) neural imaging and language. The volume also includes an integrated reference section and a comprehensive index.
Author: David E. Rumelhart
Publisher:
ISBN: 9780262631105
Category : Artificial intelligence
Languages : en
Pages : 611
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Book Description
Author: Allan Collins
Publisher: Elsevier
ISBN: 148321446X
Category : Computers
Languages : en
Pages : 673
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Book Description
Readings in Cognitive Science: A Perspective from Psychology and Artificial Intelligence brings together important studies that fall in the intersection between artificial intelligence and cognitive psychology. This book is composed of six chapters, and begins with the complex anatomy and physiology of the human brain. The next chapters deal with the components of cognitive science, such as the semantic memory, similarity and analogy, and learning. These chapters also consider the application of mental models, which represent the domain-specific knowledge needed to understand a dynamic system or natural physical phenomena. The remaining chapters discuss the concept of reasoning, problem solving, planning, vision, and imagery. This book is of value to psychologists, psychiatrists, neurologists, and researchers who are interested in cognition.
Author: Sushil K Prasad
Publisher: Morgan Kaufmann
ISBN: 0128039388
Category : Computers
Languages : en
Pages : 359
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Book Description
Topics in Parallel and Distributed Computing provides resources and guidance for those learning PDC as well as those teaching students new to the discipline. The pervasiveness of computing devices containing multicore CPUs and GPUs, including home and office PCs, laptops, and mobile devices, is making even common users dependent on parallel processing. Certainly, it is no longer sufficient for even basic programmers to acquire only the traditional sequential programming skills. The preceding trends point to the need for imparting a broad-based skill set in PDC technology. However, the rapid changes in computing hardware platforms and devices, languages, supporting programming environments, and research advances, poses a challenge both for newcomers and seasoned computer scientists. This edited collection has been developed over the past several years in conjunction with the IEEE technical committee on parallel processing (TCPP), which held several workshops and discussions on learning parallel computing and integrating parallel concepts into courses throughout computer science curricula. - Contributed and developed by the leading minds in parallel computing research and instruction - Provides resources and guidance for those learning PDC as well as those teaching students new to the discipline - Succinctly addresses a range of parallel and distributed computing topics - Pedagogically designed to ensure understanding by experienced engineers and newcomers - Developed over the past several years in conjunction with the IEEE technical committee on parallel processing (TCPP), which held several workshops and discussions on learning parallel computing and integrating parallel concepts
Author: Dimitri Bertsekas
Publisher: Athena Scientific
ISBN: 1886529159
Category : Mathematics
Languages : en
Pages : 832
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Book Description
This highly acclaimed work, first published by Prentice Hall in 1989, is a comprehensive and theoretically sound treatment of parallel and distributed numerical methods. It focuses on algorithms that are naturally suited for massive parallelization, and it explores the fundamental convergence, rate of convergence, communication, and synchronization issues associated with such algorithms. This is an extensive book, which aside from its focus on parallel and distributed algorithms, contains a wealth of material on a broad variety of computation and optimization topics. It is an excellent supplement to several of our other books, including Convex Optimization Algorithms (Athena Scientific, 2015), Nonlinear Programming (Athena Scientific, 1999), Dynamic Programming and Optimal Control (Athena Scientific, 2012), Neuro-Dynamic Programming (Athena Scientific, 1996), and Network Optimization (Athena Scientific, 1998). The on-line edition of the book contains a 95-page solutions manual.
