The following excerpts are from an interview with Marvin Minsky which took place at his home in Brookline, Massachusetts, on January 23rd, 1991. The interview, which is included in its entirety as a Foreword in the book Understanding Music with AI: Perspectives on Music Cognition (edited by Mira Balaban, Kemal Ebcioglu, and Otto Laske), is a conversation about music, its peculiar features as a human activity, the special problems it poses for the scientist, and the suitability of AI methods for clarifying and/or solving some of these problems. The conversation is open-ended, and should be read accordingly, as a discourse to be continued at another time.

There is substantial evidence that AI technology can meet the requirements of the large potential market that will exist for knowledge-based software engineering at the turn of the century. In this article, which forms the conclusion to the AAAI Press book Automating Software Design, edited by Michael Lowry and Robert McCartney, Michael Lowry discusses the future of software engineering, and how knowledge-based software engineering (KBSE) progress will lead to system development environments. Specifically, Lowry examines how KBSE techniques promote additive programming methods and how they can be developed and introduced in an evolutionary way.

After a decade of fundamental interdisciplinary research in machine learning, the spadework in this field has been done; the 1990s should see the widespread exploitation of knowledge discovery as an aid to assembling knowledge bases. The contributors to the AAAI Press book Knowledge Discovery in Databases were excited at the potential benefits of this research. The editors hope that some of this excitement will communicate itself to "AI Magazine readers of this article.

Industrial managers, engineers, and technologists have many expectations from artificial intelligence and its application to knowledge-based systems. Although the past decade has witnessed a number of innovative applications of AI in manufacturing, the field is still in its infancy and holds even greater promise for the future. The AAAI Press book Artificial Intelligence Applications in Manufacturing, (from which the following article was selected) presents a number of articles that relate to the enhancement of planning and decision making capabilities in today's automated production environments.

As a communication scholar, I am This latest computer revolution well aware that many traditionalists has taken shape only within the view the respective disciplines of past five years. My recently completed These two revolutions have been master's thesis argues against this operating independently with limited view. Many concepts from the field success, instead of together with The workshops on Artificial Intelligence of communication have been used by potentially phenomenal success. The and Statistics have broadened the flow artificial intelligence researchers and multimedia revolution has successfully of information between the two fields scholars in the development of AI. broken into the marketplace on and encouraged interdisciplinary work. The central argument of my perspective all levels, but lacks the key component General Chair: R.W. Oldford (U. is that artificial intelligence is (symbolic reasoning) needed for Waterloo); man Program Chair: P. Cheese Sponsers: Sot. for A.I. and potential to provide the current multimedia By transcending traditional Stats., Int'l Ass. for Stat.

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The work described in my Ph.D. dissertation (Fischer 1991)1 merges computational and cognitive investigations of abductive reasoning. It is the outcome of seven years of research focusing on abductive explanation generation and involving the departments of computer and information science, industrial and systems engineering, pathology, and allied medical professions at The Ohio State University.

The Department of Computer Science at Louisiana State University (LSU) has been involved in robotics research since 1992 when the Robotics Research Laboratory (RRL) was established as a research and teaching program specializing in autonomous mobile robots (AMRS). Researchers at RRL are conducting high-quality research in amrs with the goal of identifying the computational problems and the types of knowledge that are fundamental to the design and implementation of autonomous mobile robotic systems. In this article, we overview the projects that are currently under way at LSU's RRL.

Recent attempts to develop larger and more complex knowledge-based systems have revealed the shortcomings and problems of centralized, single-agent architectures and have acted as a springboard for research in distributed AI (DAI). Although initial research efforts in DAI concentrated on issues relating to homogeneous systems (that is, systems using agents of a similar type or with similar knowledge), there is now increasing interest in systems comprised of heterogeneous components. The workshop on cooperation among heterogeneous intelligent agents, held July 15 during the 1991 National Conference on Artificial Intelligence, was organized by Evangelos Simoudis, Mark Adler, Michael Huhns, and Edmund Durfee. It was designed to bring together researchers and practitioners who are studying how to enable a heterogeneous collection of independent intelligent systems to cooperate in solving problems that require their combined abilities.

We can take planning to be the optimization and debugging of a robot's program by reasoning about possible courses of execution. It is necessary to the extent that fragments of robot programs are combined at run time. There are several strands of research in the field; I survey six: (1) attempts to avoid planning; (2) the design of flexible plan notations; (3) theories of time-constrained planning; (4) planning by projecting and repairing faulty plans; (5) motion planning; and (6) the learning of optimal behaviors from reinforcements. However, we are already beginning to see how to mesh plan execution with plan generation and learning.