Localized representation and planning methods for parallel domains

Authors:
Amy L. Lansky;David S. Fogelsong
Affiliations:
Artificial Intelligence Center, SRI International, Menlo Park, California, and the Center for the Study of Language and Information, Stanford University;Computer Science Department, Stanford University
Venue:
AAAI'87 Proceedings of the sixth National conference on Artificial intelligence - Volume 1
Year:
1987

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Abstract

This paper presents a general method for structuring domains that is based on the notion of locality. We consider a localized domain description to be one that is partitioned into regions of activity, each of which has some independent significance. The use of locality can be very beneficial for domain representation and reasoning, especially for parallel, muItiagent domains. We show how localized domain descriptions can alleviate aspects of the frame problem and serve as the foundation of a planning technique based on localized planning spaces. Because domain constraints and properties are localized, potential interactions among these search spaces are fewer and more easily identified.