Intelligence takes many forms. This exciting study explores the novel insight, based on well-established ethological principles, that animals, humans, and autonomous robots can all be analyzed as multi-task autonomous control systems. Biological adaptive systems, the authors argue, can in fact provide a better understanding of intelligence and rationality than that provided by traditional AI.
Intentions in Communication brings together major theorists from artificial intelligence and computer science, linguistics, philosophy, and psychology whose work develops the foundations for an account of the role of intentions in a comprehensive theory of communication.
Explanation and Interaction describes the problems and issues involved in generating interactive user-sensitive explanations. It presents a particular computational system that generates tutorial, interactive explanations of how simple electronic circuits work. However, the approaches and ideas in the book can be applied to a wide range of computer applications where complex explanations are provided, such as documentation, advisory, and expert systems.
In this provocative book, Lance Rips describes a unified theory of natural deductive reasoning and fashions a working model of deduction, with strong experimental support, that is capable of playing a central role in mental life.
Classical computationalism—-the view that mental states are computational states—-has come under attack in recent years. Critics claim that in defining computation solely in abstract, syntactic terms, computationalism neglects the real-time, embodied, real-world constraints with which cognitive systems must cope.
The psychologist William James observed that "a native talent for perceiving analogies is ... the leading fact in genius of every order." The centrality and the ubiquity of analogy in creative thought have been noted again and again by scientists, artists, and writers, and understanding and modeling analogical thought have emerged as two of the most important challenges for cognitive science.
Computational modeling plays a central role in cognitive science. This book provides a comprehensive introduction to computational models of human cognition. It covers major approaches and architectures, both neural network and symbolic; major theoretical issues; and specific computational models of a variety of cognitive processes, ranging from low-level (e.g., attention and memory) to higher-level (e.g., language and reasoning). The articles included in the book provide original descriptions of developments in the field.
This wide-ranging collection of essays is inspired by the memory of the cognitive psychologist John Macnamara, whose influential contributions to language and concept acquisition have provided the basis for numerous research programs. The areas covered by the essays include the foundations of language and thought, congnitive and linguistic development, and mathematical approaches to cognition.
Einstein said that "the whole of science is nothing more than a refinement of everyday thinking." David Klahr suggests that we now know enough about cognition—and hence about everyday thinking—to advance our understanding of scientific thinking. In this book he sets out to describe the cognitive and developmental processes that have enabled scientists to make the discoveries that comprise the body of information we call "scientific knowledge."
In Mind and Mechanism, Drew McDermott takes a computational approach to the mind-body problem (how it is that a purely physical entity, the brain, can have experiences). He begins by demonstrating the falseness of dualist approaches, which separate the physical and mental realms. He then surveys what has been accomplished in artificial intelligence, clearly differentiating what we know how to build from what we can imagine building.