Foundations Of Artificial Intelligence
Have the classical methods and ideas of AI outlived their usefulness? Foundations of Artificial Intelligence critically evaluates the fundamental assumptions underpinning the dominant approaches to AI. In the 11 contributions, theorists historically associated with each position identify the basic tenets of their position. They discuss the underlying principles, describe the natural types of problems and tasks in which their approach succeeds, explain where its power comes from, and what its scope and limits are. Theorists generally skeptical of these positions evaluate the effectiveness of the method or approach and explain why it works - to the extent they believe it does - and why it eventually fails.
David Kirsh is Assistant Professor in the Department of Cognitive Science at the University of California, San Diego.
Contents: Foundations of AI: The Big Issues, D. Kirsh. Logic and Artificial Intelligence, N. J. Nilsson. Rigor Mortis: A Response to Nilsson's 'Logic and Artificial Intelligence,' L. Birnbaum. Open Information Systems Semantics for Distributed Artificial Intelligence, C. Hewitt. Social Conceptions of Knowledge and Action: DAI Foundations and Open Systems Semantics, L. Gasser. Intelligence without Representation, R. A. Brooks. Today the Earwig, Tomorrow Man? D. Kirsh. On the Thresholds of Knowledge, D. B. Lenat, E. A. Feigenbaum. The Owl and the Electric Encyclopedia, B. C. Smith. A Preliminary Analysis of the Soar Architecture as a Basis for General Intelligence, P. S. Rosenbloom, J. E. Laird, A. Newell, R. McCarl. Approaches to the Study of Intelligence, D. A. Norman.