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Proceedings Paper

Variable-Based Intelligent Backtracking
Author(s): V. Rajasekar; M. Narasimha Murty
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Paper Abstract

In this paper we present a new scheme for intelligent backtracking in Horn-Clause programs. It is to be observed that variables give more information about the cause of the failure rather than predicates. The scheme suggested in this paper, makes use of this information to eliminate a lot of redundant backtracking. This scheme suggested requires less overhead as compared to the scheme suggested by Vipin Kumar and is easy to implement. Our scheme makes use of an observation that a variable's instantiated value is not altered unless there is a failure on this variable and the system backtracks to the step at which this variable got instantiated. Such a feature is not exploited by conventional Prolog interpreters. We present an algorithm for the proposed intelligent backtracking scheme. We illustrate this scheme with examples. The extra overhead required by this algorithm is the failure list that contains the list of variables that could have caused the failure, changed list that contains the list of variables whose values have changed during backtracking, and the variable look-up table that contains the step numbers, wherein the variables got instantiated.

Paper Details

Date Published: 21 March 1989
PDF: 10 pages
Proc. SPIE 1095, Applications of Artificial Intelligence VII, (21 March 1989); doi: 10.1117/12.969356
Show Author Affiliations
V. Rajasekar, Indian Institute of Science (India)
M. Narasimha Murty, Indian Institute of Science (India)

Published in SPIE Proceedings Vol. 1095:
Applications of Artificial Intelligence VII
Mohan M. Trivedi, Editor(s)

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