Prolog Meta-Interpreters for Rule-Based Inference Under Uncertainty

and

Uncertain facts and inexact rules can be represented and processed in standard Prolog through meta-interpretation. This requires the specification of appropriate parsers and belief calculi. We present a meta-interpreter that takes a rule-based belief calculus as an external variable. The certainty-factors calculus and a heuristic Bayesian belief-update model are then implemented as stand-alone Prolog predicates. These, in turn, are bound to the meta-interpreter environment through secondĀ­ order programming. The resulting system is a powerful experimental tool which enables inquiry into the impact of various designs of belief calculi on the external validity of expert systems. The paper also demonstrates the (well-known) role of Prolog meta-interpreters in building expert system shells.


  • 6815153 bytes

prolog, rules, uncertainty

TechReport

New York University

Graduate School of Business Administration

Downloads: 10 downloads

UMBC ebiquity