Second, I was one of the few academic AI AAAI can encourage practitioners to Corporate functions. Applications researchers who attended some sessions make their data available to researchers. In addition to helping researchers in used in successful applications. AI research is relevant to the prob-in this regard. University of California Second, my research has recently at Irvine focused on learning methods that If you have a track record of successfully revise the knowledge base of an expert developing and deploying system when the expert system conflicts knowledge based systems to solve with an expert's decision on a real-world problems, and you wish set of examples.

Decision analysis and expert systems are technologies intended to support human reasoning and decision making by formalizing expert knowledge so that it is amenable to mechanized reasoning methods. Despite some common goals, these two paradigms have evolved divergently, with fundamental differences in principle and practice. Recent recognition of the deficiencies of traditional AI techniques for treating uncertainty, coupled with the development of belief nets and influence diagrams, is stimulating renewed enthusiasm among AI researchers in probabilistic reasoning and decision analysis. We present the key ideas of decision analysis and review recent research and applications that aim toward a marriage of these two paradigms. This work combines decision-analytic methods for structuring and encoding uncertain knowledge and preferences with computational techniques from AI for knowledge representation, inference, and explanation. We end by outlining remaining research issues to fully develop the potential of this enterprise.

Review of Knowledge-Based Design Systems

Building new knowledge-based systems today usually entails constructing new knowledge bases from scratch. System developers would then only need to worry about creating the specialized knowledge and reasoners new to the specific task of their system. This approach would facilitate building bigger and better systems cheaply. This article presents a vision of the future in which knowledge-based system development and operation is facilitated by infrastructure and technology for knowledge sharing.

This article describes a task-specific, domain-independent architecture for candidate evaluation. I discuss the task-specific architecture approach to knowledge-based system development. Finally, I describe a task-specific expert system shell, which includes a development environment (Ceved) and a run-time consultation environment (Ceval). This shell enables nonprogramming domain experts to easily encode and represent evaluation-type knowledge and incorporates the encoded knowledge in performance systems.

Building new knowledge-based systems today usually entails constructing new knowledge bases from scratch. It could instead be done by assembling reusable components. System developers would then only need to worry about creating the specialized knowledge and reasoners new to the specific task of their system. This new system would interoperate with existing systems, using them to perform some of its reasoning. In this way, declarative knowledge, problem- solving techniques, and reasoning services could all be shared among systems. This approach would facilitate building bigger and better systems cheaply. The infrastructure to support such sharing and reuse would lead to greater ubiquity of these systems, potentially transforming the knowledge industry. This article presents a vision of the future in which knowledge-based system development and operation is facilitated by infrastructure and technology for knowledge sharing. It describes an initiative currently under way to develop these ideas and suggests steps that must be taken in the future to try to realize this vision.

There has been a good deal of discussion recently about the possibility of standardizing knowledge representation efforts, including the development of an interlingua, or knowledge interchange format (KIF), that would allow developers of declarative knowledge to share their results with other AI researchers. In this article, I examine the practicality of this idea. I present some philosophical arguments against it, describe a straw-man KIF, and suggest specific experiments that would help explore these issues.

Each is supported and work to find a general solution to that by a formalized theory of the moves in the class of problems.

The applications include the user-advised construction of an assembly line balancing system and a self-optimizing street light control system. The generalized production-rule strategy that is better than any other at Arizona State University. The estimation is based on for the decision maker to respond to. The system can serve as a module simulation models. of an expert system in need of numeric Figure 1 shows the or functional estimates of hiddenvariable Mazur, Robert F. geographically distributed input Cromp, Bede McCall, operations and knowledge bases. Bickmore, Jan van been in the area of forecasting and Leeuwen, João Martins, interpolating econometric indicators.

The design constructs about the functional aspects of these can be no more general than the Reviewed by Amit Mukerjee prototypes. A harbinger of actions, information that can then be learning and vocabulary inadequacy) change is perhaps the book Knowledge-Based used to refine or adapt the prototype may be why the authors turn to analog Design Systems by R. D. to meet the design goals. Coyne, M. A. Rosenman, A. D. Radford, problem is then reduced to the problem Where the book falls short is in M. Balachandran, and J. S. Gero of searching through these possible illustrating the difference between (Addison Wesley, Reading, Mass., control actions to identify a the design task and other traditional 1990, 567 pages): It presents the sequence that will result in the desired Much of the discussion concentrates view because the volume is based on techniques are used in this process. Some of the other problems encountered here will also planning-type search through a space issues that one would have thought be different. Indeed, it seems in vision, planning, learning, and so resulting in conflicting criteria that clear that a large number of design on.