The Cambridge Handbook of Artificial Intelligence

The Cambridge Handbook of Artificial Intelligence

Keith Frankish

Language: English

Pages: 365

ISBN: 0521691915

Format: PDF / Kindle (mobi) / ePub


Artificial intelligence, or AI, is a cross-disciplinary approach to understanding, modeling, and creating intelligence of various forms. It is a critical branch of cognitive science, and its influence is increasingly being felt in other areas, including the humanities. AI applications are transforming the way we interact with each other and with our environment, and work in artificially modeling intelligence is offering new insights into the human mind and revealing new forms mentality can take. This volume of original essays presents the state of the art in AI, surveying the foundations of the discipline, major theories of mental architecture, the principal areas of research, and extensions of AI such as artificial life. With a focus on theory rather than technical and applied issues, the volume will be valuable not only to people working in AI, but also to those in other disciplines wanting an authoritative and up-to-date introduction to the field.

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will execute or abstain from executing and when). For example, an Offer(x, y, δi, t1) means that the negotiation process will start at time t1 with agent x offering agent y a deal δi from the set of potential deals, typically of the form “I will do action 1 in exchange for action 2” or {Do(x, a1), Do(y, a2)}. Then, in the next negotiation step, agent y will counteroffer, either with Accept(y, δi, t2), in which case the negotiation episode ends with the implementation of the agreement, δi; or with

Intelligence 47: 139–59. Chalmers, D. (1990). Why Fodor and Pylyshyn were wrong: The simplest refutation, in Proceedings of the 12th Annual Conference of the Cognitive Science Society (pp. 340–7). Hillsdale, NJ: Lawrence Erlbaum. Church, A. (1936). An unsolvable problem of elementary number theory, American Journal of Mathematics 58: 345–63. Davis, R., Buchanan, B., and Shortliffe, E. (1977). Production rules as a representation for a knowledge-based consultation program, Artificial

2009), New Waves in Philosophy of Action (with Jesús H. Aguilar and Andrei A. Buckareff, 2010), and The Cambridge Handbook of Cognitive Science (with William M. Ramsey, Cambridge, 2012). Stan Franklin is the W. Harry Feinstone Interdisciplinary Research Professor at the University of Memphis and Co-director of its Institute for Intelligent Systems. He is the author of Artificial Minds (1995) as well as numerous articles and book chapters on cognitive modeling, artificial general intelligence,

arms supporting the weights are mechanically linked to a valve that varies steam pressure inversely to the height of the weights. The result of this arrangement is to keep the engine speed within a narrow range, even when load on the drive shaft varies. Van Gelder suggested that if we are trying to understand cognition, the Watt governor is a better inspiration than computers. The key point of contrast is that the governor’s system of linkages performs its useful function without having any part

superficially like “one” problem. The “How many eggs…?” example illustrates the importance of hierarchy and sequential order: The parsing simply could not be accomplished without getting these right. And precision, too, is crucial – for a single letter can sometimes make a huge difference. (Compare a telegram saying “Our son is dead” with one saying “Your son is dead.”) However, precision can be overdone. The early GOFAI programs were notoriously brittle, in the sense that missing and/or

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