Collects the thoughts of almost two hundred of today's leading thinkers on the issue of artifical intelligence.

This book is a collection of writings by active researchers in the field of Artificial General Intelligence, on topics of central importance in the field. Each chapter focuses on one theoretical problem, proposes a novel solution, and is written in sufficiently non-technical language to be understandable by advanced undergraduates or scientists in allied fields. This book is the very first collection in the field of Artificial General Intelligence (AGI) focusing on theoretical, conceptual, and philosophical issues in the creation of thinking machines. All the authors are researchers actively developing AGI projects, thus distinguishing the book from much of the theoretical cognitive science and AI literature, which is generally quite divorced from practical AGI system building issues. And the discussions are presented in a way that makes the problems and proposed solutions understandable to a wide readership of non-specialists, providing a distinction from the journal and conference-proceedings literature. The book will benefit AGI researchers and students by giving them a solid orientation in the conceptual foundations of the field (which is not currently available anywhere); and it would benefit researchers in allied fields by giving them a high-level view of the current state of thinking in the AGI field. Furthermore, by addressing key topics in the field in a coherent way, the collection as a whole may play an important role in guiding future research in both theoretical and practical AGI, and in linking AGI research with work in allied disciplines

In these essays Heinz von Foerster discusses some of the fundamental principles that govern how we know the world and how we process the information from which we derive that knowledge. Included are path- breaking articles concerning the principles of computation in neural nets (1967), the definition of self-organizing systems (1960), the nature of cognition (1970), as well as recent expansions on these themes (e.g. "How recursive is communication," 1993). Working with Norbert Wiener, Warren McCullough, and others in the 1960s and 1970s, von Foerster was one of the founders of the science of cybernetics, which has had profound effects both on modern systems theory and on the philosophy of cognition. At the Biological Computer Laboratory at the University of Illinois he produced the first parallel computers and contributed to many other developments in the theory of computation and cognition.

Joe Messenger is an award-winning specialist in artificial intelligence. The son of a cryonics pioneer, he believes that people can be made to live forever. But he also knows that merely freezing the body is not enough; without one's brain - one's consciousness - a cryonically preserved person will be incomplete. Joe, a computer genius, devises a way to download the human brain into a supercomputer called ARCHIVE. Joe's wife, Karen, finds his cutting-edge research increasingly disturbing, particularly his obsessive work on ARCHIVE, which is developing signs of a distinct and sinister personality. Karen's complaint that ARCHIVE is beginning to dominate their lives is not idle paranoia - it is truer than even she realizes. Karen and Joe's marriage is further threatened when he falls for Juliet Spring, a gifted young scientist whose loveliness is matched by her keen insight into Joe's work. But just as the pair are on the brink of a scientific breakthrough, a series of macabre accidents befall Joe, Karen, and their son, Jack - clearly the work of some malevolent force. It becomes increasingly evident that the obsessions that have shaped Joe's life are about to blow his family apart.

Computers And Thought by Edward A. Feigenbaum is a comprehensive book that explores the relationship between computers and human thought. The book delves into the history of computer science and artificial intelligence, and how these fields have impacted our understanding of human cognition. It also examines the ways in which computers have been used to model human thought processes, and how these models have been applied to various fields such as psychology, linguistics, and philosophy.Feigenbaum discusses the different approaches to artificial intelligence, including rule-based systems, expert systems, and neural networks. He also explores the limitations of these approaches and the challenges of creating truly intelligent machines. The book includes case studies of successful applications of artificial intelligence, such as the development of chess-playing programs and natural language processing systems.The author also addresses ethical and philosophical questions related to artificial intelligence, such as the possibility of machines surpassing human intelligence and the implications of this for society. He argues that while computers can simulate human thought processes, they cannot replicate the full range of human experience and consciousness.Overall, Computers And Thought is a thought-provoking and informative book that provides a comprehensive overview of the relationship between computers and human thought. It is a valuable resource for anyone interested in the history and future of artificial intelligence and its impact on society.This scarce antiquarian book is a facsimile reprint of the old original and may contain some imperfections such as library marks and notations. Because we believe this work is culturally important, we have made it available as part of our commitment for protecting, preserving, and promoting the world's literature in affordable, high quality, modern editions, that are true to their original work.

What’s the most useful thing you could know about your own life? In this era-defining book, developed from her groundbreaking Radio 4 essay series, Naomi Alderman turns her boundless curiosity and incisive thinking to a question that affects us all: how do we understand, and navigate, the epoch we’re living through? She calls this epoch the Information Crisis. The internet has flooded us with more knowledge, opinions, ideas, opportunities, as well as verbal attacks and misinformation, than ever before. It lets us learn more quickly and also spread falsehood more quickly, it brings us together and also divides us in new ways, it is now the lens through which we perceive and understand the world. There is no going back. But we have been here before. In fact, this is humanity’s third information crisis. The first, the invention of writing 5,000 years ago, and the second, the invention of the printing press 600 years ago, drastically reshaped our perceptions, interactions and mental landscapes in ways that feel acutely familiar. Overwhelmed by information, people become afraid and angry, unsettled and distressed, as well as more knowledgeable, educated and curious. By looking at those previous information crises, both the turmoil and the advances, Alderman asks what we can learn from the past to better understand our present, and prepare for our future. Drawing on the work of philosophers and historians, Don’t Burn Anyone at the Stake Today explores how new technology opens up new ways of being and helps us chart a way forward (once again), through the turbulent seas of information overload.[Bokinfo]

Abstract In this chapter we provide an overview of probabilistic logic networks (PLN), including our motivations for developing PLN and the guiding principles underlying PLN. We discuss foundational choices we made, introduce PLN knowledge representation, and briefly introduce inference rules and truth-values. We also place PLN in context with other approaches to uncertain inference. 1.1 Motivations This book presents Probabilistic Logic Networks (PLN), a systematic and pragmatic framework for computationally carrying out uncertain reasoning – r- soning about uncertain data, and/or reasoning involving uncertain conclusions. We begin with a few comments about why we believe this is such an interesting and important domain of investigation. First of all, we hold to a philosophical perspective in which “reasoning” – properly understood – plays a central role in cognitive activity. We realize that other perspectives exist; in particular, logical reasoning is sometimes construed as a special kind of cognition that humans carry out only occasionally, as a deviation from their usual (intuitive, emotional, pragmatic, sensorimotor, etc.) modes of thought. However, we consider this alternative view to be valid only according to a very limited definition of “logic.” Construed properly, we suggest, logical reasoning may be understood as the basic framework underlying all forms of cognition, including those conventionally thought of as illogical and irrational.

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When it was first published in 1972, Hubert Dreyfus's manifesto on the inherent inability of disembodied machines to mimic higher mental functions caused an uproar in the artificial intelligence community. The world has changed since then. Today it is clear that "good old-fashioned AI," based on the idea of using symbolic representations to produce general intelligence, is in decline (although several believers still pursue its pot of gold), and the focus of the Al community has shifted to more complex models of the mind. It has also become more common for AI researchers to seek out and study philosophy. For this edition of his now classic book, Dreyfus has added a lengthy new introduction outlining these changes and assessing the paradigms of connectionism and neural networks that have transformed the field. At a time when researchers were proposing grand plans for general problem solvers and automatic translation machines, Dreyfus predicted that they would fail because their conception of mental functioning was naive, and he suggested that they would do well to acquaint themselves with modern philosophical approaches to human beings. What Computers Can't Do was widely attacked but quietly studied. Dreyfus's arguments are still provocative and focus our attention once again on what it is that makes human beings unique.

Style is a fundamental aspect of the human experience, yet exactly what it is and how it works are elusive. Exploring the issue from a computational viewpoint, this book shows how information is deployed in the production and perception of different styles.

In the High Bay at the Robotics Institute at Carnegie Mellon, Segways scoot across the floor chasing soccer balls while other robots hunt for treasure. Nursebots, developed to care for hospital patients, mingle with a robotic Lara Croft look-alike. Lee Gutkind immersed himself in this frenzied subculture and, in Almost Human, introduces us to Zoë, Groundhog, Grace, and Sandstorm -- robots designed to help, or in some cases replace, humans -- as well as to the colorful cast of researchers attempting to create language to talk not only to machines but also to one another across their disciplines. - from publisher description

Parsing the Turing Test is a landmark exploration of both the philosophical and methodological issues surrounding the search for true artificial intelligence. Will computers and robots ever think and communicate the way humans do? When a computer crosses the threshold into self-consciousness, will it immediately jump into the Internet and create a World Mind? Will intelligent computers someday recognize the rather doubtful intelligence of human beings? Distinguished psychologists, computer scientists, philosophers, and programmers from around the world debate these weighty issues – and, in effect, the future of the human race – in this important volume.

Book by Richard E. Bellman

In this monograph, the authors propose a systematic and rigorous treatment of electromagnetic field representations in complex structures. The architecture suggested in this book accommodates use of different numerical methods as well as alternative Green's function representations in each of the subdomains resulting from a partitioning of the overall problem. The subdomains are regions of space where electromagnetic energy is stored and are described in terms of equivalent circuit representations based either on lumped element circuits or on transmission lines. Connection networks connect the subcircuits representing the subdomains. The connection networks are lossless, don't store energy and represent the overall problem topology. This is similar to what is done in circuit theory and permits a phrasing of the solution of EM field problems in complex structures by Network-oriented methods.

Preamble The emergence of machine intelligence during the second half of the twentieth century is the most important development in the evolution of this planet since the origin of life two to three thousand million years ago. The emergence of machine intelligence within the matrix of human society is analogous to the emergence, three billion years ago, of complex, self-replicating molecules within the matrix of an energy-rich molecular soup - the first step in the evolution of life. The emergence of machine intelligence within a human social context has set into motion irreversible processes which will lead to an evolutionary discontinuity. Just as the emergence of "Life" represented a qualitatively different form of organisation of matter and energy, so will pure "Intelligence" represent a qualitatively different form of organisation of matter, energy and life. The emergence of machine intelligence presages the progression of the human species as we know it, into a form which, at present, we would not recognise as "human". As Forsyth and Naylor (1985) have pointed out: "Humanity has opened two Pandora's boxes at the same time, one labelled genetic engineering, the other labelled knowledge engineering. What we have let out is not entirely clear, but it is reasonable to hazard a guess that it contains the seeds of our successors".

Logic is now widely recognized to be one of the foundational disciplines of computing and has found applications in virtually all aspects of the subject, from software engineering and hardware to programming languages and artificial intelligence. There is a growing need for an in-depth survey of the applications in logic in A1 and computer science. The Handbook of Logic in Ariticial Intelligence and Logic Programming and its companion, the Handbook of Logic in Computer Science, have been created in response to this need. We see the creation of the Handbook as a combination of authoritative exposition, comprehensive survey, and fundamental research exploring the underlying themes in the various areas. The intended audience is graduate students and researchers in the areas of A1 and logic, as well as other people interested in the subject. We assume as background some mathematical sophistication. Much of the material will be of interest to logicians and mathematicians. The tables of contents of the volumes were finalized after extensive discussions between handbook authors and second readers. The first volumes present the logical foundations and deduction methodologies extensively used in A1. Volumes 3 and 4 cover reasoning, and Volume 5 details logic programming. The chapters which in many cases are of monograph length and scope, emphasize possible unifying themes. They are written by internationally renowned researchers in the respective areas. The chapters are co-ordinated and their contents have been reviewed in joint meetings.