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The Real Estate Agent: Modeling Users By Uncertain Reasoning

AI Magazine

Two topics are treated here. First we present a user model patterned after the stereotype approach (Rich, 1979). This model surpasses Rich's model with respect to it's greater flexibility in the construction of user profiles, and it's treatment of positive and negative arguments. Second, we present an inference machine. This machine treats uncertain knowledge in the form of evidence for and against the accuracy of a proposition. Truth values are replaced by the concept of two-dimensional evidence space. We discuss the consequences of the concept, particularly with regard to verification. The connection between these two topics is established by implementation of the user model on the inference machine.



Artificial Intelligence Research Capabilities of the Air Force Institute of Technology

AI Magazine

The Air Force Institute of Technology (AFIT) provides master's degree education to Air Force and Army Officers in various engineering fields It is in a unique position to educate and perform research in the area of applications of artificial intelligence to military problems. Its two AI faculty members are the only military officers with PhD's in Artificial Intelligence. In the past two years, the artificial intelligence Laboratory of AFIT has become a major focal point for AI research and applications within the government. In this article, we describe our on-going applications research in the areas of automated cockpit systems, natural language understanding, maintenance expert systems, expert systems for planning and knowledge based software design.


Learning Language Using a Pattern Recognition Approach

AI Magazine

A pattern recognition algorithm is described that learns a transition net grammar from positive examples. Two sets of examples -- one in English and one in Chinese -- are presented. It is hoped that language learning will reduce the knowledge acquisition effort for expert systems and make the natural language interface to database systems more transportable. The algorithm presented makes a step in that direction by providing a robust parser and reducing special interaction for introduction of new words and terms.


Artificial Intelligence Research in France

AI Magazine

In the first section, some characteristic features of AI research in France are presented, including difficulties with the current means and the current organization of AI research. In the second section, the state-of-the-art in different areas of AI is described. Besides some weakness, and in spite of the general difficulties mentioned in the first section, strong points and great potentialities are exhibited. This allows us to conclude that AI research in France may play an important part at the international level, if the necessary means for its development in the middle and long term are given.


By-Laws of Association for the Advancement of Artificial Intelligence

AI Magazine

I Section 6. Resignation: Any member may resign by filing a written resignation with the Secretary-Treasurer. Section 7. Reinstatement: Upon written request by a Section 2. Other Ofices: The corporation may have former member filed with the Secretary-Treasurer, the Executive such other offices, either within or without the County of Council, by majority vote, may reinstate a former San Mateo, State of California, as the Executive Council member. Section 8. Transfer of Membership: Membership in this corporation is not transferable or assignable. Section 1. Classes of Members: The corporation shall Section 1. Annual Meetang: The annual meeting of the have two classes of members: Regular and Student. Student Corporation will take place during its Annual Conference.


Artificial Intelligence Research Capabilities of the Air Force Institute of Technology

AI Magazine

The Air Force Institute of Technology (AFIT) provides master's degree education to Air Force and Army Officers in various engineering fields It is in a unique position to educate and perform research in the area of applications of artificial intelligence to military problems. Its two AI faculty members are the only military officers with PhD's in Artificial Intelligence. In the past two years, the artificial intelligence Laboratory of AFIT has become a major focal point for AI research and applications within the government. In this article, we describe our on-going applications research in the areas of automated cockpit systems, natural language understanding, maintenance expert systems, expert systems for planning and knowledge based software design.


Scientific DataLink's Artificial Intelligence Classification Scheme

AI Magazine

About a year ago. I was approached by Phoebe Huang of Comtex Scientific Corporation who hoped that I would help devise a dramatically expanded index for topics in AI to aid Comtex in indexing the series of AI memos and reports that they had been gathering. Comtex had tried to get the ACM to expand and update its classification. But was told that ACM had just revised the listing two years ago or so ago, and did not intend to revise it again for a while: even if they did. The revision might require a year or more to complete. Comtex wanted the new classification within six to eight weeks. I agreed to take on the task, thinking it wouldn't be too hard. The major decision I had to make was whether to use the existing ACM index scheme and add to it, or start with a fresh sheet of paper and devise my own. I decided to stick with ACM's top two levels, only adding, not modifying, major headings.


Contributors to the Spring Issue of AI Magazine

AI Magazine

Tin Nguyen performed the work contained in the article "Knowledge Base Verification" while at Lockheed and is currently working for Bell Northern Research as a member of the research staff. Deanne Pecora, a staff engineer with the Lockheed Artificial Intelligence Center, 2710 Sand Hill Road, Menlo Park, California 94025, is working on Rick Brigs, author of "Knowledge Representation and Inference in Sanskrit: A applying knowledge-based systems to Review of the First National Conference," is a senior engineer at Delfin Systems, real problems. She is a coauthor of 1349 Moffett Park Drive, Sunnyvale, California 94089. Briggs is currently working'Knowledge Base Verification." Walt Perkins, coauthor of "Knowledge Base Verification" is a consulting scientist Lindley Darden, who wrote "Viewing the History of Science as Compiled Hindsight," with the Lockheed Artificial is an associate professor in the departments of philosophy and history and Intelligence Center, 2710 Sand Hill a member of the graduate faculty in the Committee on the History and Philosophy Road, Menlo Park, California 94025 of Science at the University of Maryland, College Park. She is currently and the principal developer of the serving in the second year of a halftime research appointment at the University Lockheed expert system. of Maryland Institute for Advanced Computer Studies. Her mailing address is Department of Philosophy, University of Maryland, College Park, Maryland David Prerau is a principal member of 20742. The primary responsibility is to lead the author of "The 1985 Workshop on Distributed Artificial Intelligence, he is currently development of major expert systems working in the area of distributed artificial intelligence and is organizing with high corporate payoff and impact.


An Overview of the KL-ONE Knowledge Representation System

Classics

KL-ONE is a system for representing knowledge in Artificial Intelligence programs. It has been developed and refined over a long period and has been used in both basic research and implemented knowledge-based systems in a number of places in the AI community. Here we present the kernel ideas of KL-ONE, emphasizing its ability to form complex structured descriptions. In addition to detailing all of KL-ONE's description-forming structures, we discuss a bit of the philosophy underlying the system, highlight notions of taxonomy and classification that are central to it, and include an extended example of the use of KL-ONE and its classifier in a recognition task. This research was supported in part by the Defense Advanced Research Projects Agency under Contract N00014-77-C-0378. Views and conclusions contained in this paper are the authors' and should not be interpreted as representing the official opinion or policy of DARPA, the U.S. Government, or any person or agency connected with them.