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• Philosophical foundations / Andy Clark
• Planning and problem solving / Robert Inder
• Representation of knowledge / Derek Partridge
• Machine learning / Stuart Russell
• Connectionism and neural networks / Harry Barrow
• Expert systems and theories of knowledge / John Fox
• Machine vision / David C. Hogg
• Natural language processing / Mark Steedman
• Creativity / Margaret A. Boden
• Human-computer interaction / Mike Sharples
• Artificial life and the animat approach to artificial intelligence / Jean-Arcady Meyer.

• A logical calculus of the ideas immanent in nervous activity, Warren S.McCulloch and Walter H.Pitts
• computing machinery and intelligence, Alan M.Turing
• minds, brains and programs, John R.Searle
• escaping from the Chinese room, Margaret A.Boden
• computer science as empirical enquiry - symbols and search, Allen Newell and Herbert A.Simon
• artificial intelligence - a personal view, David C.Marr
• cognitive wheels - the frame problem of AI, Daniel C. Dennett
• the naive physics manifesto, Patrick J.Hayes
• a critique of pure reason, Drew McDermott
• motives, mechanisms and emotions, Aaron Sloman
• distributed representations, Geoffrey E.Hinton et al
• connectionism, competence and explanation, Andy Clark
• making a mind versus modelling the brain - artificial intelligence back at a branch-point, Hubert L.Dreyfus and Stuart E.Dreyfus
• some reductive strategies in cognitive neurobiology, Paul M.Churchland.
• (source: Nielsen Book Data)

• Introduction
• Warren S. McCulloch and Walter H. Pitts: A Logical Calculus of Nervous Activity
• Alan M. Turing: Computing Machinery and Intelligence
• John R. Searle: Minds, Brains, and Programs
• Margaret A. Boden: Escaping from the Chinese Room
• Allen Newell and Herbert A. Simon: Computer Science as Empirical Enquiry: Symbols and Search
• David C. Marr: Artificial Intelligence: A Personal View
• Daniel C. Dennett: Cognitive Wheels: The Frame Problem of AI
• Patrick J. Hayes: The Naive Physics Manifesto
• Drew McDermott: A Critique of Pure Reason
• Aaron Sloman: Motives, Mechanisms, and Emotions
• Geoffrey E. Hinton, James L. McClelland, and David E. Rumelhart: Distributed Representations
• Andy Clark: Connectionism, Competence, and Explanation
• Hubert L. Dreyfus and Stewart E. Dreyfus: Making a Mind Versus Modelling the Brain
• Paul M. Churchland: Some Reductive Strategies in Cognitive Neurobiology
• Adrian Cussins: The Connectionist Construction of Concepts.
• (source: Nielsen Book Data)

This collection of essays looks into the philosophical arguments behind artificial intelligence and whether one can equate such concepts as intelligence, understanding and thinking to computers. Classic arguments, such as the Chinese room are discussed as well as modern arguments, such as if one should differentiate between the connectionist computers and the digital computers. There is an introduction written by the editor, who is a leading name in artificial intelligence and upholds the view that, given time, computers will be able to match humans in intelligence.
(source: Nielsen Book Data)
Is 'artificial intelligence' a contradiction in terms? Could computers (in principle) model every aspect of the mind, including logic, language, and emotion? What of the more brain-like, connectionist computers: could they really understand, even if digital computers cannot? This collection of classic and contemporary readings (which includes an editor's introduction and an up-to-date reading list) provides a clearly signposted pathway into hotly disputed philosophical issues at the heart of artificial intelligence.
(source: Nielsen Book Data)

• A. Clark, Philosophical Foundations. R. Inder, Planning and Problem Solving. D. Partridge, Representation of Knowledge. S. Russell, Machine Learning. H. Barrow, Connectionism and Neural Networks. J. Fox, Expert Systems and Theories of Knowledge. D.C. Hogg, Machine Vision. M. Steedman, Natural Language Processing. M.A. Boden, Creativity. M. Sharples, Human-Computer Interaction. J.-A. Meyer, Artificial Life and the Animate Approach to Artificial Intelligence. Chapter References. Index.
• (source: Nielsen Book Data)

Artificial Intelligence is the study of how to build or program computers to enable them to do what minds can do. This volume discusses the ways in which computational ideas and computer modeling can aid our understanding of human and animal minds. Major theoretical approaches are outlined, as well as some promising recent developments. Fundamental philosophical questions are discussed along with topics such as: the differences between symbolic and connectionist AI, planning and problem solving, knowledge representation, learning, expert systems, vision, natural language, creativity, and human-computer interaction. This volume is suitable for any psychologist, philosopher, or computer scientist wanting to know the current state of the art in this area of cognitive science.
(source: Nielsen Book Data)