A Bibliography on Hybrid Reasoning

The Spring Symposium on Knowledge-based Environments for Teaching and Learning focused on the use of technology to facilitate learning, training, teaching, counseling, coaxing and coaching.

Based on the experience in manufacturing production scheduling problems which the AI community has amassed over the last ten years, a workshop was held to provide a forum for discussion of the issues encountered in the design of AI-based scheduling systems. Several topics were addressed including: the relative virtues of expert system, deep method, and interactive approaches, the balance between predictive and reactive components in a scheduling system, the maintenance of convenient scheduling descriptions, the application of the ideas of chaos theory to scheduling, the state of the art in schedulers which learn, and the practicality and desirability of a set of benchmark scheduling problems. This article expands on these issues, abstracts the papers which were presented, and summarizes the lengthy discussions that took place.

The Full-Sized Knowledge-Based Systems Research Workshop was held May 7-8, 1990 in Washington, D.C., as part of the AI Systems in Government Conference sponsored by IEEE Computer Society, Mitre Corporation and George Washington University in cooperation with AAAI. The goal of the workshop was to convene an international group of researchers and practitioners to share insights into the problems of building and deploying Full-Sized Knowledge Based Systems (FSKBSs).

This symposium was very successful and was perhaps the most unusual of the spring symposia this year. It brought together for the first time distinguished researchers from many diverse disciplines to discuss and share results on a particular topic of mutual interest. The disciplines included machine learning, computational learning theory, computer vision, pattern recognition, perceptual psychology, statistics, information theory, theoretical computer science, and molecular biology, with the involvement of the latter group having lead to a joint session with the AI and Molecular Biology symposium.

Truth maintenance is a collection of techniques for doing belief revision. A truth maintenance system's task is to maintain a set of beliefs in such a way that they are not known to be contradictory and no belief is kept without a reason. Truth maintenance systems were introduced in the late seventies by Jon Doyle and in the last five years there has been an explosion of interest in this kind of systems. In this paper we present an annotated bibliography to the literature of truth maintenance systems, grouping the works referenced according to several classifications.

The 1988 Workshop on Principles of Hybrid Reasoning, a one-day AAAI-sponsored workshop, was held in St. Paul, Minnesota on August 21, 1988, in conjunction with the National Conference on Artificial Intelligence. This article reports on the workshop and presents some of our afterthoughts based upon prolonged discussion of the issues that arose during the workshop.

This bibliography was originally compliled for and distributed at the 1988 Workshop on Principles of Hybrid Reasoning. This bibliography was originally compliled for and distributed at the 1988 Workshop on Principles of Hybrid Reasoning.

With increases in the complexity of information that must be communicated either by or to computer comes a corresponding need to find ways to communicate that information simply and effectively. It makes little sense to force the burden of communication on a single medium, restricted to just one of spoken or written text, gestures, diagrams, or graphical animation, when in many situations information is only communicated effectively through combinations of media.