LANSKY@SRI-AI.ARPA (05/08/86)
GRANULARITY Jerry R. Hobbs (HOBBS@SRI-AI) Artificial Intelligence Center, SRI International CSLI, Stanford University 11:00 AM, MONDAY, May 12 SRI International, Building E, Room EJ228 (new conference room) We look at the world under various grain sizes and abstract from it only those things that serve our present interests. We can view a road,for example, as a line, a surface, or a volume. Such abstractions enable us to reason about situations without getting lost in irrelevant complexities. Knowledge-rich intelligent systems will have to have similar capabilities. In this talk I will present a framework in which we can understand such systems. In this framework, a knowledge base consists of a global theory together with a large number of relatively simple, idealized, grain-dependent local theories, interrelated by articulation axioms. In a complex situation, the crucial features are abstracted from the environment, determining a granularity, and the corresponding local theory is selected. This is the only computation done in the global theory. The local theory is then applied in the bulk of the problem-solving process. When shifts in perspective are required, articulation axioms are used to translate the problem and partial results from one local theory to another. In terms of this framework, I will discuss idealization, the concepts of supervenience and reducibility, prototype-deformation types of description, and the emergence of global properties from local phenomena, and the relationship of granularity to circumscription. Several examples of uses of this framework from a wide variety of applications will be given. VISITORS: Please arrive 5 minutes early so that you can be escorted up from the E-building receptionist's desk. Thanks!