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| Title: | Using the Parka Parallel Knowledge Representation System (Version 3.2) |
| Authors: | Kettler, Brian
Andersen, William
Hendler, James
Luke, Sean |
| Type: | Technical Report |
| Issue Date: | 15-Oct-1998 |
| Series/Report no.: | UM Computer Science Department; CS-TR-3485
UMIACS; UMIACS-TR-95-68 |
| Abstract: | Parka is a symbolic, semantic network knowledge representation system
that takes advantage of the massive parallelism of supercomputers such
as the Connection Machine. The Parka language has many of the
features of traditional semantic net/frame-based knowledge
representation languages but also supports several kinds of rapid
parallel inference mechanisms that scale to large knowledge-bases of
hundreds of thousands of frames or more. Parka is intended for
general-purpose use and has been used thus far to support A.I. systems
for case-based reasoning and data mining.
This document is a user manual for the current version of Parka,
version 3.2. It describes the Parka language and presents some
examples of knowledge representation using Parka. Details about the
parallel algorithms, implementation, and empirical results are
presented elsewhere.
(Also cross-referenced as UMIACS-TR-95-68) |
| URI: | http://hdl.handle.net/1903/736 |
| Appears in Collections: | Technical Reports of the Computer Science Department
Technical Reports from UMIACS
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