What can computers do in principle? What are their inherent theoretical limitations? These are questions to which computer scientists must address themselves. The theoretical framework which enables such questions to be answered has been developed over the last fifty years from the idea of a computable function: intuitively a function whose values can be calculated in an effective or automatic way. This book is an introduction to computability theory (or recursion theory as it is traditionally known to mathematicians). Dr Cutland begins with a mathematical characterisation of computable functions using a simple idealised computer (a register machine); after some comparison with other characterisations, he develops the mathematical theory, including a full discussion of non-computability and undecidability, and the theory of recursive and recursively enumerable sets. The later chapters provide an introduction to more advanced topics such as Gildel's incompleteness theorem, degrees of unsolvability, the Recursion theorems and the theory of complexity of computation. Computability is thus a branch of mathematics which is of relevance also to computer scientists and philosophers. Mathematics students with no prior knowledge of the subject and computer science students who wish to supplement their practical expertise with some theoretical background will find this book of use and interest.

This systematic investigation of computation and mental phenomena by a noted psychologist and computer scientist argues that cognition is a form of computation, that the semantic contents of mental states are encoded in the same general way as computer representations are encoded. It is a rich and sustained investigation of the assumptions underlying the directions cognitive science research is taking.

Since its publication in 1949, D.O. Hebb's, The Organization of Behavior has been one of the most influential books in the fields of psychology and neuroscience. However, the original edition has been unavailable since 1966, ensuring that Hebb's comment that a classic normally means "cited but not read" is true in his case. This new edition rectifies a long-standing problem for behavioral neuroscientists--the inability to obtain one of the most cited publications in the field.
The Organization of Behavior played a significant part in stimulating the investigation of the neural foundations of behavior and continues to be inspiring because it provides a general framework for relating behavior to synaptic organization through the dynamics of neural networks.
D.O. Hebb was also the first to examine the mechanisms by which environment and experience can influence brain structure and function, and his ideas formed the basis for work on enriched environments as stimulants for behavioral development.
References to Hebb, the Hebbian cell assembly, the Hebb synapse, and the Hebb rule increase each year. These forceful ideas of 1949 are now applied in engineering, robotics, and computer science, as well as neurophysiology, neuroscience, and psychology--a tribute to Hebb's foresight in developing a foundational neuropsychological theory of the organization of behavior.

In bringing together seminal articles on the foundations of research, the first volume of Neurocomputing has become an established guide to the background of concepts employed in this burgeoning field. Neurocomputing 2 collects forty-one articles covering network architecture, neurobiological computation, statistics and pattern classification, and problems and applications that suggest important directions for the evolution of neurocomputing.James A. Anderson is Professor in the Department of Cognitive and Linguistic Sciences at Brown University. Andras Pellionisz is a Research Associate Professor in the Department of Physiology and Biophysics at New York Medical Center and a Senior National Research Council Associate to NASA. Edward Rosenfeld is editor and publisher of the newsletters Intelligence and Medical Intelligence.

Researchers will find Neurocomputing an essential guide to the concepts employed in this field that have been taken from disciplines as varied as neuroscience, psychology, cognitive science, engineering, and physics. A number of these important historical papers contain ideas that have not yet been fully exploited, while the more recent articles define the current direction of neurocomputing and point to future research. Each article has an introduction that places it in historical and intellectual perspective.
Included among the 43 articles are the pioneering contributions of McCulloch and Pitts, Hebb, and Lashley; innovative work by Von Neumann, Minsky and Papert, Cooper, Grossberg, and Kohonen; exciting new developments in parallel distributed processing.

Man has within a single generation found himself sharing the world with a strange new species: the computers and computer-like machines. Neither history, nor philosophy, nor common sense will tell us how these machines will affect us, for they do not do "work" as did machines of the Industrial Revolution. Instead of dealing with materials or energy, we are told that they handle "control" and "information" and even "intellectual processes." There are very few individuals today who doubt that the computer and its relatives are developing rapidly in capability and complexity, and that these machines are destined to play important (though not as yet fully understood) roles in society's future. Though only some of us deal directly with computers, all of us are falling under the shadow of their ever-growing sphere of influence, and thus we all need to understand their capabilities and their limitations. It would indeed be reassuring to have a book that categorically and systematically described what all these machines can do and what they cannot do, giving sound theoretical or practical grounds for each judgment. However, although some books have purported to do this, it cannot be done for the following reasons: a) Computer-like devices are utterly unlike anything which science has ever considered---we still lack the tools necessary to fully analyze, synthesize, or even think about them; and b) The methods discovered so far are effective in certain areas, but are developing much too rapidly to allow a useful interpretation and interpolation of results. The abstract theory---as described in this book---tells us in no uncertain terms that the machines' potential range is enormous, and that its theoretical limitations are of the subtlest and most elusive sort. There is no reason to suppose machines have any limitations not shared by man.

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.