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The Rise of the Expert Company: How Visionary Companies Are Using Artificial Intelligence to Achieve Higher Productivity and Profits
Feigenbaum, E. A. | McCorduck, P. | Nii, H. P.
"This is a popular interpretation of expert systems - computer models providing artificial intelligence to managers and businessmen - which are transforming business in the 1980s. The book gives an inside view of many international companies such as Canon, Westinghouse, IBM, Du Pont and others." New York: Times Books.
Multistage negotiation in distributed planning
Conry, S. E. | Meyer, R. A. | Lesser, V. R.
In A. H. Bond and L. Gasser (Eds.), Readings in distributed artificial intelligence. San Mateo, Calif.: Morgan Kaufmann, 367- 384
The CDP: A unifying formulation for heuristic search, dynamic programming, and branch-and-bound
In Kanal, L. N. and Kumar, V. (Eds.), Search in Artificial Intelligence, chap. 1, pp. 1โ27. Springer-Verlag.
Formulation of Tradeoffs in Planning under Uncertainty
In this proposal, I describe a. method for formulating plans from
Setting up large-scale qualitative models
Proceedings of the Seventh National Conference on Artificial Intelligence: 301-306
The Yale Artificial Intelligence Project: A Brief History
In the restaurant script, notated as $RESTAURANT, the roles might directly to the United Press International Yale researchers explored intentionality include customer, waitress, and cook; news wire and could skim news One of the earliest programs to the props could be a menu, table, and stories in dozens of different domains, embody goals and plans within the silverware; the locations could be the and produce summaries in several languages. CD paradigm was Jim Meehan's bar, dining area, and kitchen; and the On the DEC-20 (which by TALESPIN, which made up stories events would include arriving, seating, 1978 had replaced the PDP-101, similar to the fables of Aesop.
An Assessment of Tools for Building Large Knowledge-Based Systems
A number of tools that support the development, execution, and maintenance of knowledge-based systems are marketed commercially. Many of these tools, however, are designed for applications that can be executed on personal computers and are not suitable for building large knowledge-based systems. The market for knowledge engineering tools designed for applications that require the computational power of a Lisp machine or an engineering workstation is dominated by a few vendors. This article is an assessment of the current state of tools used to build large knowledge-based systems. This assessment is based on the collective strengths and weaknesses of several tools that have been evaluated. In addition, an estimate is made of the features that will be required in the next generation of tools.
