Derek Partridge – författare

This outstanding collection is designed to address the fundamental issues and principles underlying the task of Artificial Intelligence. The editors have selected not only papers now recognized as classics but also many specially commissioned papers which examine the methodological and theoretical foundations of the discipline from a wide variety of perspectives: computer science and software engineering, cognitive psychology, philosophy, formal logic and linguistics. Carefully planned and structured, the volume tackles many of the contentious questions of immediate concern to AI researchers and interested observers. Is Artificial Intelligence in fact a discipline, or is it simply part of computer science? What is the role of programs in AI and how do they relate to theories? What is the nature of representation and implementation, and how should the challenge of connectionism be viewed? Can AI be characterized as an empirical science? The comprehensiveness of this collection is further enhanced by the full, annotated bibliography. All readers who want to consider what Artificial Intelligence really is will find this sourcebook invaluable, and the editors will undoubtedly succeed in their secondary aim of stimulating a lively and continuing debate.

Managers, business owners, computer literate individuals, software developers, students, and researchers--all are looking for an understanding of artificial intelligence (AI) and what might be in the future. In this literate yet easy-to-read discussion, Derek Partridge explains what artificial intelligence can and cannot do, and what it holds for applications such as banking, financial services, and expert systems of all kinds. Topics include: the strengths and weaknesses of software development and engineering; machine learning and its promises and problems; expert systems and success stories; and practical software through artificial intelligence.

IT systems explode budget estimates, bust production deadlines by years, and then fail to work properly. Why this IT-system crisis? Poor programmers? Inadequate project management? No.The Seductive Computer argues that the fundamental nature of programming technology itself is the real culprit; it promises perfection but can only deliver emergent chaos. It is also an insidiously compelling technology, peculiarly male oriented. IT systems, an unavoidable and increasing reality in all our lives, are something new to man - large-scale discrete complexity. The Seductive Computer explains this novelty that defies human understanding.This book illustrates in a simple yet thorough manner the underlying concepts necessary for understanding the IT-system crisis - not ‘How To Program’ but what the demands of programming are. It then proceeds to lay out the full gamut of issues - all stemming from the nature of the technology.From development to maintenance IT-system personnel are grappling with incipient chaos. The technicians are seduced by the detailed challenge of the technology. The scientists are seduced by the promises of their technology. The managers and users are seduced by the mysteries of the technology. No IT system is ever fully understood by anyone, so surprising behaviours will always emerge.What can be done? We must rein in our expectations of IT systems: what they can do, and how reliably they can do it. On the positive side, The Seductive Computer discusses novel paradigms that look beyond the current discrete technology: neural computing and precise approximation computing.

From Black Holes and Big Bangs to the Higgs boson and the infinitesimal building blocks of all matter, modern science has been spectacularly successful, with one glaring exception — intelligence. Intelligence still remains as one of the greatest mysteries in science.How do you chat so effortlessly? How do you remember, and why do you forget? From a basis of ten maxims What Makes You Clever explains the difficulties as well as the persuasive and persistent over-estimations of progress in Artificial Intelligence. Computers have transformed our lives, and will continue to do so for many years to come. But ever since the Turing Test proposed in 1950 up to IBM's Deep Blue computer that won the second six-game match against world champion Garry Kasparov, the science of artificial intelligence has struggled to make progress.The reader's expertise is engaged to probe human language, machine learning, neural computing, holistic systems and emergent phenomenon. What Makes You Clever reveals the difficulties that scientists grapple with in their efforts to understand your cleverness, and points to possible ways forward.

From Black Holes and Big Bangs to the Higgs boson and the infinitesimal building blocks of all matter, modern science has been spectacularly successful, with one glaring exception — intelligence. Intelligence still remains as one of the greatest mysteries in science.How do you chat so effortlessly? How do you remember, and why do you forget? From a basis of ten maxims What Makes You Clever explains the difficulties as well as the persuasive and persistent over-estimations of progress in Artificial Intelligence. Computers have transformed our lives, and will continue to do so for many years to come. But ever since the Turing Test proposed in 1950 up to IBM's Deep Blue computer that won the second six-game match against world champion Garry Kasparov, the science of artificial intelligence has struggled to make progress.The reader's expertise is engaged to probe human language, machine learning, neural computing, holistic systems and emergent phenomenon. What Makes You Clever reveals the difficulties that scientists grapple with in their efforts to understand your cleverness, and points to possible ways forward.

This volume is a broad-based collection of chapters that address the areas of overlap between the fields of artificial intelligence (AI) and software engineering. A taxonomy of this overlap area is developed and related to other major attempts to address the interaction between these two fields. Each of the four major subareas-AI-based support environments, software engineering toolds and techniques, methodological issues of AI software development, and AI techniques in practical software is described and illustrated with representative examples.

In this textbook the author endeavors to cover the large and growing field of artificial intelligence (AI) in some detail. While there are books that examine and discuss global perspectives on AI, they make no attempt to cover the diversity of theories and programs. A global perspective on the subject is provided by this volume, but in conjunction with an exhaustive survey of the field. It covers all recognized AI work in sufficient detail to allow a critiquie from general concerns to be anchored, whenever possible, in the structure of specific AI programs. It can be used as a supplement to other AI texts, providing broader perspectives on the wealth of details that such texts contain. It can also be considered as a companion to the current AI literature for it is only in conference proceedings and journals that these up-to-date details are usually found.

After introducing the concept of artificial intelligence (AI), the authors of this text discuss the scope and limitations of AI technology in the various subfields that are expected to be relevant to business management systems - natural language processing, voice processing, image processing, and intelligent robots. The authors survey each subfield in some detail, not because they expect business managers to absorb all the technical details but because a proper appreciation of the potential of AI technology must be founded on the technicalities of the discipline. Therefore, substantial detail and follow-up references are provided for the reader to explore to whatever depth seems most appropriate. The authors also take a close look at expert systems technology as this subfield of AI has a reasonable claim to be the major commercialization of AI technology to date. They discuss the scope and limitations of this particular technology, and present its advantages and disadvantages with respect to applications in business.Having surveyed the technical possibilities, the authors present the resources for AI that are available: technical resources, both software and hardware, and human resources. In the final part of the book they examine the likely impacts of AI technology from the management perspective.

After introducing the concept of artificial intelligence (AI), the authors of this text discuss the scope and limitations of AI technology in the various subfields that are expected to be relevant to business management systems - natural language processing, voice processing, image processing, and intelligent robots. The authors survey each subfield in some detail, not because they expect business managers to absorb all the technical details but because a proper appreciation of the potential of AI technology must be founded on the technicalities of the discipline. Therefore, substantial detail and follow-up references are provided for the reader to explore to whatever depth seems most appropriate. The authors also take a close look at expert systems technology as this subfield of AI has a reasonable claim to be the major commercialization of AI technology to date. They discuss the scope and limitations of this particular technology, and present its advantages and disadvantages with respect to applications in business.Having surveyed the technical possibilities, the authors present the resources for AI that are available: technical resources, both software and hardware, and human resources. In the final part of the book they examine the likely impacts of AI technology from the management perspective.

Aimed at the computer-literate person wishing to find out about the reality of exploiting the promise of artificial intelligence (AI) in practical, maintainable software systems, this text tries to avoid the hype usually associated with the subject. Instead, it presents the realities, the problems, the current state of the art, and future directions. Throughout, the reader will find a comprehensive and coherent examination of the many problems that engineering AI software involves, as well as a consideration of the alternative routes to solution of these problems.