To choose their actions, reasoning programs must be able to make assumptions and subsequently revise their beliefs when discoveries contradict these assumptions. The Truth Maintenance System (TMS) is a problem solver subsystem for performing these functions by recording and maintaining the reasons for program beliefs. Such recorded reasons are useful in constructing explanations of program actions and in guiding the course of action of a problem solver. This paper describes (1) the representations and structure of the TMS, (2) the mechanisms used to revise the current set of beliefs, (3) how dependency-directed backtracking changes the current set of assumptions, (4) techniques for summarizing explanations of beliefs, (5) how to organize problem solvers into "dialectically arguing" modules, (6) how to revise models of the belief systems of others, and (7) methods for embedding control structures in patterns of assumptions. We stress the need of problem solvers to choose between alternative systems of beliefs, and outline a mechanism by which a problem solver can employ rules guiding choices of what to believe, what to want, and what to do.Artificial Intelligence 12(3):231-272

This report describes a knowledge-base system in which the information is stored in a network of small parallel processing elements??de and link units??ich are controlled by an external serial computer. This network is similar to the semantic network system of Quillian, but is much more tightly controlled. Such a network can perform certain critical deductions and searches very quickly; it avoids many of the problems of current systems, which must use complex heuristics to limit and guided their searches. It is argued (with examples) that the key operation in a knowledge-base system is the intersection of large explicit and semi-explicit sets. The parallel network system does this in a small, essentially constant number of cycles; a serial machine takes time proportional to the size of the sets, except in special cases.

This approach leads to an infinite sequence of algorithms I. Surface Models

In J. E. Hayes, D. Michie, and L. I. Mikulich (Eds.), Machine Intelligence 9. Chichester, England: Ellis Horwood Ltd., 149-195

Doctoral dissertation, Computer ScienceDept., Stanford University.

The purpose of the Acoustical Society of America is to generate, disseminate, and promote the knowledge and practical applications of acoustics. Established in 1929, the present membership includes leaders in acoustics worldwide. Diverse fields of interest in acoustics include physics, engineering, architecture, noise, oceanography, biology, speech and hearing, psychology and music. The purpose of the Society is to generate, disseminate, and promote the knowledge and practical applications of acoustics.

Cognitive Science, vol. 3, No. 1, pp. 67-90.

IJCAI 6, 269-274.

In Metzing, D. (Ed.), Frame Conceptions and Text Understanding, pp. 46–61. de Gruyter.

Our purpose in studying natural language understanding in conjunction with problem solving is to bring together the constraints of what formal representation can actually be obtained with the question of what knowledge is required in order to solve a wide range of problems in a semantically rich domain. We believe that these issues cannot sensibly be tackled in isolation. In practical terms we have had the benefits of an increased awareness of common problems in both areas and a realisation that some of our techniques are applicable to both the control of inference and the control of parsing. Early work on solving mathematical problems stated in natural language was done by Bobrow (STUDENT - (i]) and Chamiak (CARPS - [5]). However the rudimentary parsing and simple semantic structures used by Bobrow and Charniak are inadequate for any but the easiest problems. Our intention has been to build on B/RG Chris This work was supported by SRC grant number 94493 and an SRC research studentship for Mellish.