From one of the leading researchers in the field of human memory comes the new edition of a truly integrative perspective on learning and memory! Rather than forge a simple synthesis, Anderson integrates learning research on animals and memory research on humans without distorting the character of either one. The result is a more complete picture of learning, including material on skill acquisition, inductive learning, and applications to education.

This book achieves a goal that was set 25 years ago when the HAM theory of human memory was published. This theory reflected one of a number of then-current efforts to create a theory of human cognition that met the twin goals of precision and complexity. Up until then the standard for precision had been the mathematical theories of the 1950s and 1960s. These theories took the form of precise models of specific experiments along with some informal, verbally-stated understanding of how they could be extended to new experiments. They seemed to fall far short of capturing the breadth and power of human cognition that was being demonstrated by the new experimental work in human cognition. The next 10 years saw two major efforts to address the problems of scope. In 1976, the ACT theory was first described and included a production rule system of procedural memory to complement HAM's declarative memory. This provided a computationally adequate system which was indeed capable of accounting for all sorts of cognition. In 1993, a new version of ACT--ACT-R--was published. This was an effort to summarize the theoretical progress made on skill acquisition in the intervening 10 years and to tune the subsymbolic level of ACT-R with the insights of the rational analysis of cognition. Although the appearance of generally-available, full-function code set off a series of events which was hardly planned, it resulted in this book. The catalyst for this was the emergence of a user community. Lebiere insisted that assembling a critical mass of users was essential to the ultimate success of the theory and that a physical gathering was the only way to achieve that goal. This resulted in the First Annual ACT-R Summer School and Workshop, held in 1994. In writing the book, the authors became seized by an aspiration that went beyond just describing the theory correctly. They decided to try to display what the theory could do by collecting together and describing some of its in-house applications. This book reflects decades of work in ACT-R accumulated by many researchers. The chapters are authored by the people that did that particular work. No doubt the reader will be impressed by the scope of the research and the quality of the individual work. Less apparent, but no less important, was the effort that everyone put into achieving the overall consistency and technical integrity of the book. This is the first work in cognitive science to precisely model such a wide range of phenomena with a single theory.

Now available in paper, The Architecture of Cognition is a classic work that remains relevant to theory and research in cognitive science. The new version of Anderson's theory of cognitive architecture -- Adaptive Control of Thought (ACT*) -- is a theory of the basic principles of operation built into the cognitive system and is the main focus of the book.

Does a knowledge of Latin facilitate he learning of computer programming? Does skill in geometry make it easier to learn music? The issue of the transfer of learning from one domain to another is a classic problem in psychology as well as an educational question of great importance, which this ingenious new book sets out to solve through a theory of transfer based on a comprehensive theory of skill acquisition. The question was first studies systematically at the turn of the century by the noted psychologist Edward L. Thorndike, who proposed a theory of transfer based on common elements in two different tasks. Since then, psychologists of different theoretical orientations--verbal learning, gestalt, and information processing--have addressed the transfer question with differing and inconclusive results. Singley and Anderson resurrect Thorndike's theory of identical elements, but in a broader context and from the perspective of cognitive psychology. Making use o a powerful knowledge-representation language, they recast his elements into units of procedural and declarative knowledge in the ACT* theory of skill acquisition. One skill will transfer to another, they argue, to the extent that it involves the same productions or the same declarative precursors. They show that with production rules, ransfer can be localized to specific components--in keeping with Thorndike's theory--and yet still be abstract and mentalistic. The findings of this book have important implications for psychology and the improvement of teaching. They will interest cognitive scientists and educational psychologists, as well as computer scientists interested in artificial intelligence and cognitive modeling.

Since the publication of the first edition in 1966, Eye and Brain has established itself worldwide as an essential introduction to the basic phenomena of visual perception. In this book, Richard L. Gregory offers clear explanations of how we see brightness, movement, color, and objects, and he explores the phenomena of visual illusions to establish principles about how perception normally works and why it sometimes fails. Although successive editions have incorporated new discoveries and ideas, Gregory completely revised and updated the book for this publication, adding more than thirty new illustrations. The phenomena of illusion continue to be a major theme in the book, in which the author makes a new attempt to provide a comprehensive classification system. There are also new sections on what babies see and how they learn to see, on motion perception, and tantalizing glimpses of the relationship between vision and consciousness and of the impact of new brain imaging techniques. In addition, the presentation of the text and illustrations has been improved by the larger format and new page design. The thousands of readers of the previous editions of Eye and Brain will find this new revised edition even more attractive and enthralling.

This book is for students and researchers who have a specific interest in learning and memory and want to understand how computational models can be integrated into experimental research on the hippocampus and learning. It emphasizes the function of brain structures as they give rise to behavior, rather than the molecular or neuronal details. It also emphasizes the process of modeling, rather than the mathematical details of the models themselves.The book is divided into two parts. The first part provides a tutorial introduction to topics in neuroscience, the psychology of learning and memory, and the theory of neural network models. The second part, the core of the book, reviews computational models of how the hippocampus cooperates with other brain structures--including the entorhinal cortex, basal forebrain, cerebellum, and primary sensory and motor cortices--to support learning and memory in both animals and humans. The book assumes no prior knowledge of computational modeling or mathematics. For those who wish to delve more deeply into the formal details of the models, there are optional "mathboxes" and appendices. The book also includes extensive references and suggestions for further readings.

In eight chapters by leading researchers, Memory for Action presents our actual knowledge on memory for actions and the opposing explanaions for these phenomena. It gives an overview of the results from laboratory research on action memory and on memory for activities in social contexts, and presents recent results on memory for intended actions. Additionally, these results are put in relation to the information and to the brain modules which are necessary for successful control of actions.

This book presents a unique synthesis of the current neuroscience of cognition by one of the world's authorities in the field. The guiding principle to this synthesis is the tenet that the entirety of our knowledge is encoded by relations, and thus by connections, in neuronal networks of our cerebral cortex. Cognitive networks develop by experience on a base of widely dispersed modular cell assemblies representing elementary sensations and movements. As they develop cognitive networks organize themselves hierarchically by order of complexity or abstraction of their content. Because networks intersect profusely, sharing commong nodes, a neuronal assembly anywhere in the cortex can be part of many networks, and therefore many items of knowledge. All cognitive functions consist of neural transactions within and between cognitive networks. After reviewing the neurobiology and architecture of cortical networks (also named cognits), the author undertakes a systematic study of cortical dynamics in each of the major cognitive functions - perception, memory, attention, language, and intelligence. In this study, he makes use of a large body of evidence from a variety of methodologies, in the brain of the human as well as the nonhuman primate. The outcome of his interdisciplinary endeavor is the emergence of a structural and dynamic order in the cerebral cortex that, though still sketchy and fragmentary, mirrors with remarkable fidelity the order in the human mind.

Memory and the Computational Brain offers a provocative argument that goes to the heart of neuroscience, proposing that the field can and should benefit from the recent advances of cognitive science and the development of information theory over the course of the last several decades. A provocative argument that impacts across the fields of linguistics, cognitive science, and neuroscience, suggesting new perspectives on learning mechanisms in the brain Proposes that the field of neuroscience can and should benefit from the recent advances of cognitive science and the development of information theory Suggests that the architecture of the brain is structured precisely for learning and for memory, and integrates the concept of an addressable read/write memory mechanism into the foundations of neuroscience Based on lectures in the prestigious Blackwell-Maryland Lectures in Language and Cognition, and now significantly reworked and expanded to make it ideal for students and faculty

The hippocampus is one of a group of remarkable structures embedded within the medial temporal lobe of the brain. Long known to be important for memory, it has been a prime focus of neuroscience research for many years. The Hippocampus Book promises to facilitate developments in the field in a major way by bringing together, for the first time, contributions by leading international scientists working on hippocampal anatomy, physiology, and function. This authoritative volume offers the most comprehensive, up-to-date account of what the hippocampus does, how it does it and what happens when things go wrong. At the same time, it illustrates how research focusing on this single brain structure has revealed principles of wider generality for the whole brain in relation to anatomical connectivity, synaptic plasticity, cognition and behaviour, and computational algorithms. Well-organised in its presentation of both theory and experimental data, this peerless work vividly illustrates the astonishing progress that has been made in unravelling the workings of the brain. The Hippocampus Book is destined to take a central place on every neuroscientist's bookshelf.

本书全面讲述人工智能的发展史，几乎覆盖人工智能学科的所有领域，包括人工智能的起源。、自动定理证明、专家系统、神经网络、自然语言处理、遗传算法、深度学习、强化学习、超级智能、哲学问题和未来趋势等，以宏阔的视野和生动的语言，对人工智能进行了全面回顾和深度点评。
本书作者和书中诸多人物或为师友或相熟相知，除了详实的考证还有有趣的轶事。本书既适合专业人士了解人工智能鲜为人知的历史，也适合对人工智能感兴趣的大众读者作为入门的向导。