RUSPINI@SRI-AI.ARPA (02/25/86)
From: RUSPINI@SRI-AI.ARPA AURA (Automated Uncertainty Reasoning Assembly) is about to resume its AURAcles after some months of suspended animation. The next talk (abstract below) is scheduled for next Friday, February 28, 10AM at EK242. We plan to meet as regularly as possible each Friday thereafter at the same time. APPROXIMATE DEDUCTION IN SINGLE EVIDENTIAL BODIES Enrique H. Ruspini Artificial Intelligence Center SRI International The main objective of this talk is the review of ongoing research on the interpretation and manipulation of conditional evidence within single evidential bodies. In the context of a single body of evidence, conditional evidence is expressed as constraints on the possible values of propositional truth under the assumption that a specific proposition within the frame of discernment is known to be true. In this context deductive inference consists of the combination of the information about the probable truth of ground propositions (facts) and conditional evidence (rules) to arrive at new (a posteriori) estimates of propositional support. This process is both conceptually and procedurally different from those undertaken when several bodies of evidence are combined (e.g. using the Dempster Combination Rule). The role of conditional evidence constraints (henceforth called approximate or uncertain rules) is examined from the viewpoint of both the theory of interval probabilities and the Dempster-Shafer Calculus of Evidence. These approaches to the representation and analysis of uncertain information will be briefly described together with their theoretical underpinnings. Several possible interpretations of approximate rules will be discussed and compared. Possible approaches for the automation of approximate deduction (under each interpretation) will also be presented. Time permitting, the role of these results in the generalization of Reynold's approach to the generation of support and elementary mass measures will also be discussed. -------