Artificial Intelligence Research at the University of Michigan

The Artificial Intelligence in Medicine (AIM) Workshop has become a tradition. Meeting every year for the past nine years, it has been the forum where all the issues from basic research through applications to implementations have been discussed; it has also become a community building activity, bringing together researchers, medical practitioners, and government and industry sponsors of AIM activities.

On October 17-19 1984 a workshop on non-monotonic reasoning was held at Mohonk Mountain House, outside New Paltz, New York. The workshop was organized by Raymond Reiter and Bonnie Webber, and was sponsored by the Association for the Advancement of Artificial Intelligence.

It is interesting to note that there is no agreed upon definition of artificial intelligence. However, artificial intelligence has been around for 30 years, so one might wonder why our wheels are still spinning. Below, an attempt is made to answer this question and show why, in a serious sense, artificial intelligence can never demonstrate an outright success within its own discipline. In addition, we will see why the old bromide that "as soon as we understand how to solve a problem, it's no longer artificial intelligence" is necessarily true.

Two topics are treated here. Second, we present an inference machine. This machine treats uncertain knowledge in the form of evidence for and against the accuracy of a proposition. The connection between these two topics is established by implementation of the user model on the inference machine.

The TRW Defense Systems Group develops large man-machine networks that solve problems for government agencies. Because we have been producing first-of- a kind systems like these since the early 1950s, we consider ourselves leaders in the social art of assembling effective teams of diverse experts, and in the engineering art of conceiving and developing networks of interacting machines. Then we found that our well-worked system development techniques did not completely apply, and that our system engineering handbook needed a new chapter on communication between people and machines. We're still writing that chapter, and it won't be finished until we can add some not-yet fully developed artificial intelligence techniques.

This article presents a summary of ongoing, funded artificial intelligence research at North Carolina State University. The primary focus of the research is engineering aspects of artificial intelligence. These research efforts can be categorized into four main areas: engineering expert systems, generative database management systems, human-machine communication, and robotics and vision. The research programs are currently being sponsored by the Center for Communications and Signal Processing (CCSP), the Integrated Manufacturing Systems Engineering Institute (IMSEI), the National Aeronautics and Space Administration (NASA), the National Science Foundation (NSF) and the United States Department of Agriculture (USDA).

The AI Group at The Ohio State University conducts a broad range of research projects in knowledge-based reasoning. The primary focus of this work is on analyzing problem solving, especially within knowledge -rich domains. B. Chandrasekaran has been the director of the group since its inception in the late 1970s.

By-Laws of Association for the Advancement of Artificial Intelligence

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.