Parallel backward-chaining inference engine for production systems

Saleh M. Abu-Suod; Mehmet R. Tolun

doi:10.1117/12.56881

1 March 1992 Parallel backward-chaining inference engine for production systems

Saleh M. Abu-Suod, Mehmet R. Tolun

Proceedings Volume 1707, Applications of Artificial Intelligence X: Knowledge-Based Systems; (1992) https://doi.org/10.1117/12.56881
Event: Aerospace Sensing, 1992, Orlando, FL, United States

Abstract

In this paper, a new model to parallelize the backward-chaining inference technique in production systems called ParBack is presented. In this model, the data dependencies between rules are analyzed and then converted to special notations that constitute the search space. Parallelism is exploited in three directions: some processors are dedicated to perform the inference process; other processors perform processes that guide the inference process to the useful paths in the search space; and a third group of processors performs the rule-pruning principle that reduces the length of the paths in the search space. The results of the simulation study on ParBack show that around 850 folds of speed-up can be obtained.

Citation Download Citation

Saleh M. Abu-Suod and Mehmet R. Tolun "Parallel backward-chaining inference engine for production systems", Proc. SPIE 1707, Applications of Artificial Intelligence X: Knowledge-Based Systems, (1 March 1992); https://doi.org/10.1117/12.56881

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available