Routledge Library Editions: Artificial Intelligence - Böcker

The most exciting and productive areas of academic inquiry are often where the interests of two disciplines meet. This is certainly the case for the subject of this book, originally published in 1994, which explores the contribution that computer-based modelling and artificial intelligence can make to understanding fundamental issues in social science. Simulating Societies shows how computer simulations can help to clarify theoretical approaches, contribute to the evaluation of alternative theories, and illuminate one of the major issues of the social sciences: how social phenomena can "emerge" from individual action. The authors discuss how simulation models can be constructed using recently developed artificial intelligence techniques and they consider the methodological issues involved in using such models for theory development, testing and experiment. The introductory chapters situate the book within social science, and suggest why the time was ripe for significant progress, before defining basic terminology, showing how simulation has been used to theorize about organizations, and indicating through examples some of the fundamental issues involved in simulation. The main body of the text provides case studies drawn from economics, anthropology, archaeology, planning, social psychology and sociology.The appeal of this path-breaking book was twofold. It offered an essential introduction to simulation for social scientists and it provided case study applications for computer scientists interested in the latest advances in the burgeoning area of distributed artificial intelligence (DAI) at the time.

The most exciting and productive areas of academic inquiry are often where the interests of two disciplines meet. This is certainly the case for the subject of this book, originally published in 1994, which explores the contribution that computer-based modelling and artificial intelligence can make to understanding fundamental issues in social science. Simulating Societies shows how computer simulations can help to clarify theoretical approaches, contribute to the evaluation of alternative theories, and illuminate one of the major issues of the social sciences: how social phenomena can "emerge" from individual action. The authors discuss how simulation models can be constructed using recently developed artificial intelligence techniques and they consider the methodological issues involved in using such models for theory development, testing and experiment. The introductory chapters situate the book within social science, and suggest why the time was ripe for significant progress, before defining basic terminology, showing how simulation has been used to theorize about organizations, and indicating through examples some of the fundamental issues involved in simulation. The main body of the text provides case studies drawn from economics, anthropology, archaeology, planning, social psychology and sociology.The appeal of this path-breaking book was twofold. It offered an essential introduction to simulation for social scientists and it provided case study applications for computer scientists interested in the latest advances in the burgeoning area of distributed artificial intelligence (DAI) at the time.

Originally published in 1989 The Industrialization of Intelligence is a spirited blend of the principles of social science and computer technology. Critically praised in the United States and England by leading lights both literary and technological, it develops an original and provocative model of the interplay between computer systems and social systems.Noah Kennedy has composed a compelling story from key episodes in the development of the computer, and coupled it with a probing analysis of the true role of automation in modem society. The result firmly plants computer technology in the soil of western culture and denies the shrill claims that the information age represents a sudden break with the historical past.He starts with biographical vignettes from the lives of five pivotal thinkers, weaving their crucial insights into the larger fabric of contemporary and future society. He then gives a provocative forecast of the role of artificial intelligence in future society, and examines the probable impact of new computer technologies on employment and on the relationships between nations. The result is a reasoned understanding of our imminent future through a thoughtful analysis of our historical past.

Originally published in 1989 The Industrialization of Intelligence is a spirited blend of the principles of social science and computer technology. Critically praised in the United States and England by leading lights both literary and technological, it develops an original and provocative model of the interplay between computer systems and social systems.Noah Kennedy has composed a compelling story from key episodes in the development of the computer, and coupled it with a probing analysis of the true role of automation in modem society. The result firmly plants computer technology in the soil of western culture and denies the shrill claims that the information age represents a sudden break with the historical past.He starts with biographical vignettes from the lives of five pivotal thinkers, weaving their crucial insights into the larger fabric of contemporary and future society. He then gives a provocative forecast of the role of artificial intelligence in future society, and examines the probable impact of new computer technologies on employment and on the relationships between nations. The result is a reasoned understanding of our imminent future through a thoughtful analysis of our historical past.

The purpose of this book, originally published in 1987, was to contribute to the advance of artificial intelligence (AI) by clarifying and removing the major sources of philosophical confusion at the time which continued to preoccupy scientists and thereby impede research. Unlike the vast majority of philosophical critiques of AI, however, each of the authors in this volume has made a serious attempt to come to terms with the scientific theories that have been developed, rather than attacking superficial ‘straw men’ which bear scant resemblance to the complex theories that have been developed. For each is convinced that the philosopher’s responsibility is to contribute from his own special intellectual point of view to the progress of such an important field, rather than sitting in lofty judgement dismissing the efforts of their scientific peers.The aim of this book is thus to correct some of the common misunderstandings of its subject. The technical term Artificial Intelligence has created considerable unnecessary confusion because of the ordinary meanings associated with it, and for that very reason, the term is endlessly misused and abused. The essays collected here all aim to expound the true nature of AI, and to remove the ill-conceived philosophical discussions which seek answers to the wrong questions in the wrong ways. Philosophical discussions and decisions about the proper use of AI need to be based on a proper understanding of the manner in which AI-scientists achieve their results; in particular, in their dependence on the initial planning input of human beings. The collection combines the Anglo-Saxon school of analytical philosophy with scientific and psychological methods of investigation. The distinguished authors in this volume represent a cross-section of philosophers, psychologists, and computer scientists from all over the world. The result is a fascinating study in the nature and future of AI, written in a style which is certain to appeal and inform laymen and specialists alike.

The purpose of this book, originally published in 1987, was to contribute to the advance of artificial intelligence (AI) by clarifying and removing the major sources of philosophical confusion at the time which continued to preoccupy scientists and thereby impede research. Unlike the vast majority of philosophical critiques of AI, however, each of the authors in this volume has made a serious attempt to come to terms with the scientific theories that have been developed, rather than attacking superficial ‘straw men’ which bear scant resemblance to the complex theories that have been developed. For each is convinced that the philosopher’s responsibility is to contribute from his own special intellectual point of view to the progress of such an important field, rather than sitting in lofty judgement dismissing the efforts of their scientific peers.The aim of this book is thus to correct some of the common misunderstandings of its subject. The technical term Artificial Intelligence has created considerable unnecessary confusion because of the ordinary meanings associated with it, and for that very reason, the term is endlessly misused and abused. The essays collected here all aim to expound the true nature of AI, and to remove the ill-conceived philosophical discussions which seek answers to the wrong questions in the wrong ways. Philosophical discussions and decisions about the proper use of AI need to be based on a proper understanding of the manner in which AI-scientists achieve their results; in particular, in their dependence on the initial planning input of human beings. The collection combines the Anglo-Saxon school of analytical philosophy with scientific and psychological methods of investigation. The distinguished authors in this volume represent a cross-section of philosophers, psychologists, and computer scientists from all over the world. The result is a fascinating study in the nature and future of AI, written in a style which is certain to appeal and inform laymen and specialists alike.

This book, originally published in 1992, encapsulates ten years of research at the Open University’s Human Cognition Research Laboratory. The research investigates the problems of novice programmers, and is strongly oriented toward the design and implementation of "programming environments" aimed at eliminating or easing novices’ problems. A range of languages is studied: Pascal, SOLO, Lisp, Prolog and "Knowledge Engineering Programming". The primary emphasis of the empirical studies is to gain some understanding of novices’ "mental models" of the inner workings of computers. Such (erroneous) models are constructed by novices in their own heads to account for the idiosyncrasies of particular programming languages. The primary emphasis of the implementations described in the book is the provision of "automatic debugging aids", i.e. artificial intelligence programs which can analyse novices’ buggy programs, and make sense of them, thereby providing useful advice for the novices. Another related strand taken in some of the work is the concept of "pre-emptive design", i.e. the provision of tools such as syntax-directed editors and graphical tracers which help programmers avoid many frequently-occurring errors. A common thread throughout the book is its Cognitive Science/Artificial Intelligence orientation. AI tools are used, for instance, to construct simulation models of subjects writing programs, in order to provide insights into what their deep conceptual errors are. At the other extreme, AI programs which were developed in order to help student debug their programs are observed empirically in order to ensure that they provide facilities actually needed by real programmers. This book will be of great interest to advanced undergraduate, postgraduate, and professional researchers in Cognitive Science, Artificial Intelligence, and Human-Computer Interaction.

This book, originally published in 1992, encapsulates ten years of research at the Open University’s Human Cognition Research Laboratory. The research investigates the problems of novice programmers, and is strongly oriented toward the design and implementation of "programming environments" aimed at eliminating or easing novices’ problems. A range of languages is studied: Pascal, SOLO, Lisp, Prolog and "Knowledge Engineering Programming". The primary emphasis of the empirical studies is to gain some understanding of novices’ "mental models" of the inner workings of computers. Such (erroneous) models are constructed by novices in their own heads to account for the idiosyncrasies of particular programming languages. The primary emphasis of the implementations described in the book is the provision of "automatic debugging aids", i.e. artificial intelligence programs which can analyse novices’ buggy programs, and make sense of them, thereby providing useful advice for the novices. Another related strand taken in some of the work is the concept of "pre-emptive design", i.e. the provision of tools such as syntax-directed editors and graphical tracers which help programmers avoid many frequently-occurring errors. A common thread throughout the book is its Cognitive Science/Artificial Intelligence orientation. AI tools are used, for instance, to construct simulation models of subjects writing programs, in order to provide insights into what their deep conceptual errors are. At the other extreme, AI programs which were developed in order to help student debug their programs are observed empirically in order to ensure that they provide facilities actually needed by real programmers. This book will be of great interest to advanced undergraduate, postgraduate, and professional researchers in Cognitive Science, Artificial Intelligence, and Human-Computer Interaction.

The Soft Machine, originally published in 1985, represents a significant contribution to the study of contemporary literature in the larger cultural and scientific context. David Porush shows how the concepts of cybernetics and artificial intelligence that have sparked our present revolution in computer and information technology have also become the source for images and techniques in our most highly sophisticated literature, postmodern fiction by Barthelme, Barth, Pynchon, Beckett, Burroughs, Vonnegut and others. With considerable skill, Porush traces the growth of "the metaphor of the machine" as it evolves both technologically and in literature of the twentieth century. He describes the birth of cybernetics, gives one of the clearest accounts for a lay audience of its major concepts and shows the growth of philosophical resistance to the mechanical model for human intelligence and communication which cybernetics promotes, a model that had grown increasingly influential in the previous decade. The Soft Machine shows postmodern fiction synthesizing the inviting metaphors and concepts of cybernetics with the ideals of art, a synthesis that results in what Porush calls "cybernetic fiction" alive to the myths and images of a cybernetic age.

The Soft Machine, originally published in 1985, represents a significant contribution to the study of contemporary literature in the larger cultural and scientific context. David Porush shows how the concepts of cybernetics and artificial intelligence that have sparked our present revolution in computer and information technology have also become the source for images and techniques in our most highly sophisticated literature, postmodern fiction by Barthelme, Barth, Pynchon, Beckett, Burroughs, Vonnegut and others. With considerable skill, Porush traces the growth of "the metaphor of the machine" as it evolves both technologically and in literature of the twentieth century. He describes the birth of cybernetics, gives one of the clearest accounts for a lay audience of its major concepts and shows the growth of philosophical resistance to the mechanical model for human intelligence and communication which cybernetics promotes, a model that had grown increasingly influential in the previous decade. The Soft Machine shows postmodern fiction synthesizing the inviting metaphors and concepts of cybernetics with the ideals of art, a synthesis that results in what Porush calls "cybernetic fiction" alive to the myths and images of a cybernetic age.

Originally published in 1986, in order to probe, dispute and analyse the role of artificial intelligence in cybernetic thought and information science, the author pursues this topic within its philosophical, behavioral and neurophysiological contexts, while drawing attention to cognitive issues. By elucidating the problems and potential associated with knowledge-based systems, the book emphasized the need to examine artificial intelligence in its own right.

Originally published in 1986, in order to probe, dispute and analyse the role of artificial intelligence in cybernetic thought and information science, the author pursues this topic within its philosophical, behavioral and neurophysiological contexts, while drawing attention to cognitive issues. By elucidating the problems and potential associated with knowledge-based systems, the book emphasized the need to examine artificial intelligence in its own right.

"Artificial Intelligence" (AI) a term coined in the 1950s actually dates back as far as 1943. Now very much in the public consciousness, AI research has fallen in and out of favour over the years. Routledge Library Editions: Artificial Intelligence (10 Volumes) brings together as one set, or individual volumes, a small interdisciplinary series of previously out-of-print titles, originally published between 1970 and 1994. Covering ground in computer science, literature, philosophy, psychology, psychotherapy and sociology, this set is a fascinating insight into the development of ideas surrounding AI.

Originally published in 1988, this was the first book to examine the development, application and evaluation of computer counselling and psychotherapy. Integrating concepts of artificial intelligence and psychotherapy, this book provided extensive research data that compared the human therapist to the computer therapist at the time.This title was intended for researchers, professionals, and students of psychotherapy and artificial intelligence. By exploring the automation of therapy and the design of empathetic software this book challenges counsellors and computer scientists to look at what may have been the most fascinating topic to arise in their fields for years to come.

Originally published in 1988, this was the first book to examine the development, application and evaluation of computer counselling and psychotherapy. Integrating concepts of artificial intelligence and psychotherapy, this book provided extensive research data that compared the human therapist to the computer therapist at the time.This title was intended for researchers, professionals, and students of psychotherapy and artificial intelligence. By exploring the automation of therapy and the design of empathetic software this book challenges counsellors and computer scientists to look at what may have been the most fascinating topic to arise in their fields for years to come.

This book, originally published in 1970, concerns the new technique of computer simulation in psychology at the time. Computer programs described include models of learning, problem-solving, pattern recognition, the use of language, and personality. More general topics are discussed including the evaluation of such models, the relation of the field to cybernetics, and the problem posed by consciousness. Today it can be read and enjoyed in its historical context.

This book, originally published in 1970, concerns the new technique of computer simulation in psychology at the time. Computer programs described include models of learning, problem-solving, pattern recognition, the use of language, and personality. More general topics are discussed including the evaluation of such models, the relation of the field to cybernetics, and the problem posed by consciousness. Today it can be read and enjoyed in its historical context.

Originally published in 1995, this volume is the direct result of a conference in which a number of leading researchers from the fields of artificial intelligence and biology gathered to examine whether there was any ground to assume that a new AI paradigm was forming itself and what the essential ingredients of this new paradigm were. A great deal of scepsis is justified when researchers, particularly in the cognitive sciences, talk about a new paradigm. Shifts in paradigm mean not only new ideas but also shifts in what constitutes good problems, what counts as a result, the experimental practice to validate results, and the technological tools needed to do research. Due to the complexity of the subject matter, paradigms abound in the cognitive sciences -- connectionism being the most prominent newcomer in the mid-1980s. This workshop group was brought together in order to clarify the common ground, see what had been achieved so far, and examine in which way the research could move further. This volume is a reflection of this important meeting. It contains contributions which were distributed before the workshop but then substantially broadened and revised to reflect the workshop discussions and more recent technical work. Written in polemic form, sometimes criticizing the work done thus far within the new paradigm, this collection includes research program descriptions, technical contributions, and position papers.

Originally published in 1995, this volume is the direct result of a conference in which a number of leading researchers from the fields of artificial intelligence and biology gathered to examine whether there was any ground to assume that a new AI paradigm was forming itself and what the essential ingredients of this new paradigm were. A great deal of scepsis is justified when researchers, particularly in the cognitive sciences, talk about a new paradigm. Shifts in paradigm mean not only new ideas but also shifts in what constitutes good problems, what counts as a result, the experimental practice to validate results, and the technological tools needed to do research. Due to the complexity of the subject matter, paradigms abound in the cognitive sciences -- connectionism being the most prominent newcomer in the mid-1980s. This workshop group was brought together in order to clarify the common ground, see what had been achieved so far, and examine in which way the research could move further. This volume is a reflection of this important meeting. It contains contributions which were distributed before the workshop but then substantially broadened and revised to reflect the workshop discussions and more recent technical work. Written in polemic form, sometimes criticizing the work done thus far within the new paradigm, this collection includes research program descriptions, technical contributions, and position papers.

Originally published in 1987 when Artificial Intelligence (AI) was one of the most hotly debated subjects of the moment; there was widespread feeling that it was a field whose ‘time had come’, that intelligent machines lay ‘just around the corner’. Moreover, with the onset of the revolution in information technology and the proclamation from all corners that we were moving into an ‘information society’, developments in AI and advanced computing were seen in many countries as having both strategic and economic importance. Yet, aside from the glare of publicity that tends to surround new scientific ideas or technologies, it must be remembered that AI was a relative newcomer among the sciences; that it had often been the subject of bitter controversy; and that though it had been promising to create intelligent machines for some 40 years prior to publication, many believe that it had actually displayed very little substantive progress.With this background in mind, the aim of this collection of essays was to take a novel look at AI. Rather than following the path of old well-trodden arguments about definitions of intelligence or the status of computer chess programs, the objective was to bring new perspectives to the subject in order to present it in a different light. Indeed, instead of simply adding to the endless wrangling ‘for’ and ‘against’ AI, the source of such divisions is made a topic for analysis in its own right. Drawing on ideas from the philosophy and sociology of scientific knowledge, this collection therefore broke new ground. Moreover, although a great deal had been written about the social and cultural impact of AI, little had been said of the culture of AI scientists themselves – including their discourse and style of thought, as well as the choices, judgements, negotiations and competitive struggles for resources that had shaped the genesis and development of the paradigmatic structure of their discipline at the time. Yet, sociologists of science have demonstrated that the analysis of factors such as these is a necessary part of understanding the development of scientific knowledge. Hence, it was hoped that this collection would help to redress the imbalance and provide a broader and more interesting picture of AI.