The contributions to this workshop indicate substantial advances in the technical foundations of the field. They also show that it is time to evaluate the existing approaches to commonsense reasoning problems. The Second International Workshop on Nonmonotonic Reasoning was held from 12-16 June 1988 in Grassau, a small village near Lake Chiemsee in southern Germany. It was jointly organized by Johan de Kleer, Matthew Ginsberg, Erik Sandewall, and myself. Financial support for the workshop came from the American Association for Artificial Intelligence (AAAI), Deutsche Forschungsgemeinschaft (DFG), The European Communities (Project Cost-13), Linköping University, and SIEMENS AG.
Research on nonmonotonic temporal reasoning in general, and the Yale Shooting Problem in particular, has suffered from the absence of a criterion against which to evaluate solutions. Indeed, researchers in the area disagree not only on the solutions but also on the problems. We propose a formal yet intuitive criterion by which to evaluate theories of actions, define a monotonic class of theories that satisfy this criterion, and then provide their provably-correct nonmonotonic counterpart.
Decision theory and nonmonotonic logics are formalisms that can be employed to represent and solve problems of planning under uncertainty. We analyze the usefulness of these two approaches by establishing a simple correspondence between the two formalisms. The analysis indicates that planning using nonmonotonic logic comprises two decision-theoretic concepts: probabilities (degrees of belief in planning hypotheses) and utilities (degrees of preference for planning outcomes). We present and discuss examples of the following lessons from this decision-theoretic view of nonmonotonic reasoning: (1) decision theory and nonmonotonic logics are intended to solve different components of the planning problem; (2) when considered in the context of planning under uncertainty, nonmonotonic logics do not retain the domain-independent characteristics of classical (monotonic) logic; and (3) because certain nonmonotonic programming paradigms (for example, frame-based inheritance, nonmonotonic logics) are inherently problem specific, they might be inappropriate for use in solving certain types of planning problems. We discuss how these conclusions affect several current AI research issues.