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.

Cognitive Science: A Multidisciplinary Journal, Vol 9, No. 2, pp. 171-216, 1985

Subjects include AI's impact on employment, the AAAI conference, a response to McCarthy's Presidential Message, AI going public, and computerless expert systems.

Artificial Intelligence is rapidly leaving its academic home and moving into the marketplace. There are few precedents for an arcane academic subject becoming commercialized so rapidly. But, genetic engineering, which recently burst forth from academia to become the foundation for the hot new biotechnology industry, provides useful insights into the rites of passage awaiting the commercialization of artificial intelligence. This article examines the structural similarities and dissimilarities in the two subjects and briefly summarizes the history of the commercialization of genetic engineering. It then proposes some lessons that would benefit the artificial intelligence industry.

Research in the field of artificial intelligence is developing rapidly at the various NASA centers, including Langley research Center in Hampton, Virginia. AI studies at Langley involve research for application in aircraft flight management, remote space teleoperators and robots, and structural optimization.

In the past fifteen years artificial intelligence has changed from being the preoccupation of a handful of scientists to a thriving enterprise that has captured the imagination of world leaders and ordinary citizens alike. While corporate and government officials organize new projects whose potential impact is widespread, to date few people have been more affected by the transition than those already in the field. I review here some aspects of this transition, and pose some issues that it raises for AI researchers, developers, and leaders.

In the past fifteen years artificial intelligence has changed from being the preoccupation of a handful of scientists to a thriving enterprise that has captured the imagination of world leaders and ordinary citizens alike. While corporate and government officials organize new projects whose potential impact is widespread, to date few people have been more affected by the transition than those already in the field. I review here some aspects of this transition, and pose some issues that it raises for AI researchers, developers, and leaders.

Research in the field of artificial intelligence is developing rapidly at the various NASA centers, including Langley research Center in Hampton, Virginia. AI studies at Langley involve research for application in aircraft flight management, remote space teleoperators and robots, and structural optimization.

Originally it was Complex Information Processing. That was the name Herb Simon and I chose in 1956 to describe the area in which we are working. It didn't take long before it became Artificial Intelligence (AI). Coined by John McCarthy, that term has stuck firmly, despite continual grumblings that any other name would be twice as fair (though no grumblings by me; I like the present name). Complex Information processing lives on now only in the title of the CIP Working Papers, a series started by Herb Simon in 1956 and still accumulating entries (to 447). However, from about 1965 much of the work on artificial intelligence that was not related to psychology began to appear in technical reports of the Computer Science Department. These reports, never part of a coherent numbered series until 1978, proliferated in all directions. Starting in the early 1970s (on one can recall exactly when), they did become the subject of a general mailing and thus began to form what everyone thinks of as the CMU Computer Science Technical Reports.

During the past year, a prototype expert system for tactical data fusion has been under development,. This computer program combines various messages concerning electronic intelligence (ELINT) to aid in decision making concerning enemy actions and intentions. The prototype system is written in Prolog, a language that has proved to be very powerful and easy to use for problem /rule development. The resulting prototype system (called EXPRS-Expert Prolog System) uses English-like rule constructs of Prolog code. This approach enables the system to generate answers automatically to "why" a ruled fired, and "how" that rule fired. In addition, a rule clause construct is provided which allows direct access to Prolog code routines. This paper describes the structure of the rules used and provides typical user interactions.