50 years after the perceptron, 25 years after PDP: Neural computation in language sciences PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download 50 years after the perceptron, 25 years after PDP: Neural computation in language sciences PDF full book. Access full book title 50 years after the perceptron, 25 years after PDP: Neural computation in language sciences by Julien Mayor. Download full books in PDF and EPUB format.
Author: Julien Mayor Publisher: Frontiers E-books ISBN: 2889192571 Category : Psychology Languages : en Pages : 181
Book Description
This Research Topic aims to showcase the state of the art in language research while celebrating the 25th anniversary of the tremendously influential work of the PDP group, and the 50th anniversary of the perceptron. Although PDP models are often the gold standard to which new models are compared, the scope of this Research Topic is not constrained to connectionist models. Instead, we aimed to create a landmark forum in which experts in the field define the state of the art and future directions of the psychological processes underlying language learning and use, broadly defined. We thus called for papers involving computational modeling and original research as well as technical, philosophical, or historical discussions pertaining to models of cognition. We especially encouraged submissions aimed at contrasting different computational frameworks, and their relationship to imaging and behavioral data.
Author: Julien Mayor Publisher: Frontiers E-books ISBN: 2889192571 Category : Psychology Languages : en Pages : 181
Book Description
This Research Topic aims to showcase the state of the art in language research while celebrating the 25th anniversary of the tremendously influential work of the PDP group, and the 50th anniversary of the perceptron. Although PDP models are often the gold standard to which new models are compared, the scope of this Research Topic is not constrained to connectionist models. Instead, we aimed to create a landmark forum in which experts in the field define the state of the art and future directions of the psychological processes underlying language learning and use, broadly defined. We thus called for papers involving computational modeling and original research as well as technical, philosophical, or historical discussions pertaining to models of cognition. We especially encouraged submissions aimed at contrasting different computational frameworks, and their relationship to imaging and behavioral data.
Author: Garrison W. Cottrell Publisher: Routledge ISBN: 1317729463 Category : Psychology Languages : en Pages : 908
Book Description
This volume features the complete text of all regular papers, posters, and summaries of symposia presented at the 18th annual meeting of the Cognitive Science Society. Papers have been loosely grouped by topic, and an author index is provided in the back. In hopes of facilitating searches of this work, an electronic index on the Internet's World Wide Web is provided. Titles, authors, and summaries of all the papers published here have been placed in an online database which may be freely searched by anyone. You can reach the Web site at: http://www.cse.ucsd.edu/events/cogsci96/proceedings. You may view the table of contents for this volume on the LEA Web site at: http://www.erlbaum.com.
Author: Robert Hecht-Nielsen Publisher: Addison Wesley Publishing Company ISBN: Category : Computers Languages : en Pages : 456
Book Description
The areas covered here are those which are commonly managed by the generalist. The four contributions discuss: the autopsy in fatal non- missile head injuries; viral encephalitis and its pathology; a general approach to neuropathological problems; and dementia in middle and late life. Gives an overview of the network theory, including background review, basic concepts, associative networks, mapping networks, spatiotemporal networks, and adaptive resonance networks. Explores the principles of fuzzy logic. Annotation copyrighted by Book News, Inc., Portland, OR
Author: Peter Baumgartner Publisher: Princeton University Press ISBN: 1400863961 Category : Science Languages : en Pages : 350
Book Description
Few developments in the intellectual life of the past quarter-century have provoked more controversy than the attempt to engineer human-like intelligence by artificial means. Born of computer science, this effort has sparked a continuing debate among the psychologists, neuroscientists, philosophers,and linguists who have pioneered--and criticized--artificial intelligence. Are there general principles, as some computer scientists had originally hoped, that would fully describe the activity of both animal and machine minds, just as aerodynamics accounts for the flight of birds and airplanes? In the twenty substantial interviews published here, leading researchers address this and other vexing questions in the field of cognitive science. The interviewees include Patricia Smith Churchland (Take It Apart and See How It Runs), Paul M. Churchland (Neural Networks and Commonsense), Aaron V. Cicourel (Cognition and Cultural Belief), Daniel C. Dennett (In Defense of AI), Hubert L. Dreyfus (Cognitivism Abandoned), Jerry A. Fodor (The Folly of Simulation), John Haugeland (Farewell to GOFAI?), George Lakoff (Embodied Minds and Meanings), James L. McClelland (Toward a Pragmatic Connectionism), Allen Newell (The Serial Imperative), Stephen E. Palmer (Gestalt Psychology Redux), Hilary Putnam (Against the New Associationism), David E. Rumelhart (From Searching to Seeing), John R. Searle (Ontology Is the Question), Terrence J. Sejnowski (The Hardware Really Matters), Herbert A. Simon (Technology Is Not the Problem), Joseph Weizenbaum (The Myth of the Last Metaphor), Robert Wilensky (Why Play the Philosophy Game?), Terry A.Winograd (Computers and Social Values), and Lotfi A. Zadeh (The Albatross of Classical Logic). Speaking Minds can complement more traditional textbooks but can also stand alone as an introduction to the field. Originally published in 1995. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.
Author: Neha Yadav Publisher: Springer ISBN: 9401798168 Category : Mathematics Languages : en Pages : 114
Book Description
This book introduces a variety of neural network methods for solving differential equations arising in science and engineering. The emphasis is placed on a deep understanding of the neural network techniques, which has been presented in a mostly heuristic and intuitive manner. This approach will enable the reader to understand the working, efficiency and shortcomings of each neural network technique for solving differential equations. The objective of this book is to provide the reader with a sound understanding of the foundations of neural networks and a comprehensive introduction to neural network methods for solving differential equations together with recent developments in the techniques and their applications. The book comprises four major sections. Section I consists of a brief overview of differential equations and the relevant physical problems arising in science and engineering. Section II illustrates the history of neural networks starting from their beginnings in the 1940s through to the renewed interest of the 1980s. A general introduction to neural networks and learning technologies is presented in Section III. This section also includes the description of the multilayer perceptron and its learning methods. In Section IV, the different neural network methods for solving differential equations are introduced, including discussion of the most recent developments in the field. Advanced students and researchers in mathematics, computer science and various disciplines in science and engineering will find this book a valuable reference source.
Author: M.H. Bickhard Publisher: Elsevier ISBN: 0444825207 Category : Computers Languages : en Pages : 397
Book Description
The book focuses on a conceptual flaw in contemporary artificial intelligence and cognitive science. Many people have discovered diverse manifestations and facets of this flaw, but the central conceptual impasse is at best only partially perceived. Its consequences, nevertheless, visit themselves as distortions and failures of multiple research projects - and make impossible the ultimate aspirations of the fields. The impasse concerns a presupposition concerning the nature of representation - that all representation has the nature of encodings: encodingism. Encodings certainly exist, but encodingism is at root logically incoherent; any programmatic research predicted on it is doomed too distortion and ultimate failure. The impasse and its consequences - and steps away from that impasse - are explored in a large number of projects and approaches. These include SOAR, CYC, PDP, situated cognition, subsumption architecture robotics, and the frame problems - a general survey of the current research in AI and Cognitive Science emerges. Interactivism, an alternative model of representation, is proposed and examined.
Author: Moritz Hardt Publisher: Princeton University Press ISBN: 0691233721 Category : Computers Languages : en Pages : 321
Book Description
An authoritative, up-to-date graduate textbook on machine learning that highlights its historical context and societal impacts Patterns, Predictions, and Actions introduces graduate students to the essentials of machine learning while offering invaluable perspective on its history and social implications. Beginning with the foundations of decision making, Moritz Hardt and Benjamin Recht explain how representation, optimization, and generalization are the constituents of supervised learning. They go on to provide self-contained discussions of causality, the practice of causal inference, sequential decision making, and reinforcement learning, equipping readers with the concepts and tools they need to assess the consequences that may arise from acting on statistical decisions. Provides a modern introduction to machine learning, showing how data patterns support predictions and consequential actions Pays special attention to societal impacts and fairness in decision making Traces the development of machine learning from its origins to today Features a novel chapter on machine learning benchmarks and datasets Invites readers from all backgrounds, requiring some experience with probability, calculus, and linear algebra An essential textbook for students and a guide for researchers
Author: Julien Mayor
Author: Julien Mayor
Author: David E. Rumelhart
Author: Garrison W. Cottrell
Author: Robert Hecht-Nielsen
Author: Dan Jurafsky
Author: Ron Sun
Author: Peter Baumgartner
Author: Neha Yadav
Author: M.H. Bickhard
Author: Moritz Hardt