Massively Parallel Knowledge Representation

Inheritance Operations in Massively Parallel Knowledge Representation

Massively Parallel Simulation of Structured Connectionist Networks: An Interim Report

We map structured connectionist models of knowledge representation and reasoning onto existing general purpose massively parallel architectures with the objective of developing and implementing practical, realtime knowledge base systems. Shruti, a connectionist knowledge representation and reasoning system which attempts to model reflexive reasoning, will serve as our representative connectioni...

PARKA: A System for Massively Parallel Knowledge Representation

PARKA is a frame-based knowledge representation system implemented on massively parallel hardware--the Connection Machine (CM-2). PARKA 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. In particular, PARKA can ...

Local Consistency in Parallel Constraint-Satisfaction Networks

One of the key problems facing Artificial Intelligence (AI) is performing efficient inferences over large knowledge bases. Viewed in the context of parallel computation this problem brings forth fundamental research issues such as knowledge representation in parallel environments, problem-decomposition methods, parallelization of classes of AI problems, the role of incremental methods, parallel...

USC: description of the SNAP system used for MUC-4

The main goal of the SNAP project is to build a massively parallel computer capable of fast and accurat e natural language processing [3] . Under NSF funding, a parallel computer was built in the Parallel Knowledg e Processing Laboratory at USC and software was developed to operate the machine [2] . The approach i n designing SNAP was to find a knowledge representation and a reasoning paradigm ...