Raymond Reiter' Department of Computer Science University of Toronto Toronto, Ontario, Canada M5S-1A4 Johan de Kleer Intelligent Systems Laboratory XEROX Palo Alto Research Center 3333 Coyote Hill Road Palo Alto, California 94304 ABSTRACT In this paper we (1) define the concept of a Clause Managetnent System (CMS) A Problem-Solving Architecture Figure 1 illustrates an architecture for a problem solving system consisting of a domain dependent Reasoner coupled to a domain independent Clause Management System (CMS). For our present purposes, the Reasoner is a black box which, m the process of doing whatever it does, occasionally transmits a propositional clause 2 to the CMS.

Proceedings of AAAI-84.

In Proceedings of the Eighth IJCAI, pages 272-279. IJCAI, Karlsruhe, West Germany, August, 1983. Volume 1.

The first is to have an adequate model of the cognitive state of other agents. The second is to form plans under the constraint of resource limitations: i.e., an agent does not always have an infinite amount of time to sit and think of plans while the world changes under him; he must act. These two problems are obviously interlinked since, to have a realistic model of the cognitive states of other agents, who are presumably similar to himself, an agent must reason about the resource limitations they are subject to in reasoning about the world. In this paper we address both problems with reference to AI planning system robots and one part of their cognitive state, namely beliefs. Our goal is to pursue what might be called robot psychology: to construct a plausible model of robot beliefs by examining robots' internal representations of the world.

Over the past two years we have started a program of On the theoretical side, Professor Randall Davis has research into the development of VLSI systems. They have introduced a descriptive formalism called OMEGA, which contributes to many of the issues of Traditional automated synthesis techniques for circuit current concern in knowlege representation, and they have design are restricted to small classes of circuit functions for applied it to describe the various structured entities such as which mathematical methods exist. Sussman and his group have developed computer-aided design tools that can be of much broader assistance. Guy L. Steele developed a language to support such programming, Johan de Kleer studied causal and Professor Marvin Minsky has worked on a theory of human teleological reasoning in the recognition of circuit function thinking, which likens the mind to a society of agents and from schematics, and Howie Shrobe has worked on constraint attempts to combine a number of insights from satisfaction and the development of an interactive knowledgebased psychoanalytic, developmental, and cognitive theories of system for substantially supporting VLSI design. Further work by Richard Greenblatt and Dr. Lucia Doyle has studied belief revision via truth maintenance and Vaina develops the idea of thread memory.

Truth maintenance systems have been used in several recent problem solving systems to record justifications for deduced assertions, to track down the assumptions which underlie contradictions when they arise, and to incrementally modify assertional data structures when assumptions are retracted. A TMS algorithm is described here that is substantially different from previous systems. This algorithm performs deduction in traditional propositional logic in such a way that the premise set from which deduction is being done can be easily manipulated. A novel approach is also taken to the role of a TMS in larger deductive systems. In this approach the TMS performs all propositional deduction in a uniform manner while the larger system is responsible for controlling the instantiation of universally quantified formulae and axiom schemas.

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

All this might anyhow be called metaphysics; but it is regarded as logic when adduced as bearing on an unsolved problem, not simply as information interesting for its own sake. The only one of these which is a distinct science is evidently (2). THE UTILITY OF LOGIC That of (1) above and of (3) are evident: the interesting ones are (2) and (4).