Parallel Distributed Processing: Explorations in the Microstructure of Cognition: Volume 2: Psychological and Biological Models

What makes people smarter than computers? The work described in these two volumes suggests that the answer lies in the massively parallel architecture of the human mind. It is some of the most exciting work in cognitive science, unifying neural and cognitive processes in a highly computational framework, with links to artificial intelligence. Although thought and problem solving have a sequential character when viewed over a time frame of minutes or hours, the authors argue that each step in the sequence is the result of the simultaneous activity of a large number of simple computational elements, each influencing others and being influenced by them. Parallel Distributed Processing describes their work in developing a theoretical framework for describing this parallel distributed processing activity and in applying the framework to the development of models of aspects of perception, memory, language, and thought. Volume 2 applies to a number of specific issues in cognitive science and neuroscience. Some chapters describe models of aspects of perception, memory, language, and thought. Others discuss the relation between parallel distributed processing models and neurophysiology or describe models that are specifically addressed to neurophysiological data. The book concludes with an epilogue noting the strengths and weaknesses of the approach and directions for the future. What makes people smarter than computers? These volumes by a pioneeringneurocomputing group suggest that the answer lies in the massively parallelarchitecture of the human mind. They describe a new theory of cognition calledconnectionism that is challenging the idea of symbolic computation that hastraditionally been at the center of debate in theoretical discussions about themind.The authors' theory assumes the mind is composed of a great number ofelementary units connected in a neural network. Mental processes are interactionsbetween these units which excite and inhibit each other in parallel rather thansequential operations. In this context, knowledge can no longer be thought of asstored in localized structures; instead, it consists of the connections betweenpairs of units that are distributed throughout the network.Volume 1 lays thefoundations of this exciting theory of parallel distributed processing, while Volume2 applies it to a number of specific issues in cognitive science and neuroscience, with chapters describing models of aspects of perception, memory, language, andthought.David E. Rumelhart is Professor of Psychology at the University ofCalifornia, San Diego. James L. McClelland is Professor of Psychology atCarnegie-Mellon University. A Bradford Book. Preface......Page 4 Addresses of the PDP Research Group......Page 6 IV. PSYCHOLOGICAL PROCESSES......Page 8 14. Schemata and Sequential Thought Processes in PDP Models......Page 13 15. Interactive Processes in Speech Perception: The TRACE Model......Page 64 16. The Programmable Blackboard Model of Reading......Page 128 17. A Distributed Model ofHuman Learning and Memory......Page 176 18. On Learning the Past Tenses of English Verbs......Page 222 19. Mechanisms Processing : Assigning Roles to Constituents of Sentences......Page 278 V. BIOLOGICAL MECHANISMS......Page 332 20. Certain Aspects of the Anatomy and Physiology of the Cerebral Cortex......Page 337 21. Open Questions About Computation in Cerebral Cortex......Page 376 22. Neural and Conceptual Interpretation of PDP Models......Page 394 23. Biologically Plausible Models of Place Recognition and Goal Location......Page 436 24. State-Dependent Factors Influencing Neural Plasticity : A Partial Account of the Critical Period......Page 475 25. Amnesia and Distributed Memory......Page 507 26. Reflections on Cognition and Parallel Distributed Processing......Page 532 Future Directions......Page 548 References......Page 554 Index......Page 581 Local Disk......Page 0 file:///C|/New%20Text%20Document.txt......Page 2 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