Communications of the ACM - Special issue on parallelism
The mathematics of inheritance systems
The mathematics of inheritance systems
Case-based planning: viewing planning as a memory task
Case-based planning: viewing planning as a memory task
Terminological reasoning is inherently intractable (research note)
Artificial Intelligence
Parka: A system for massively parallel knowledge representation
Parka: A system for massively parallel knowledge representation
Building Large Knowledge-Based Systems; Representation and Inference in the Cyc Project
Building Large Knowledge-Based Systems; Representation and Inference in the Cyc Project
Active Messages: a Mechanism for Integrated Communication and
Active Messages: a Mechanism for Integrated Communication and
The tractability of path-based inheritance
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
Massively parallel memory-based parsing
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 2
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PARKA, a frame-based knowledge representation system implemented on the Connection Machine, provides a representation language consisting of concept descriptions (frames) and binary relations on those descriptions (slots). The system is designed explicitly to provide extremely fast property inheritance inference capabilities. PARKA performs fast "recognition" queries of the form "find all frames satisfying p property constraints" in O(d+p) time-proportional only to the depth, d, of the knowledge base (KB), and independent of its size. For conjunctive queries of this type, PARKA's performance is measured in tenths of a second, even for KBs with 100,000+ frames, with similar results for timings on the Cyc KB. Because PARKA's run-time performance is independent of KB size, it promises to scale up to arbitrarily larger domains. With such run-time performance, we believe PARKA is a contender for the title of "fastest knowledge representation system in the world".