KSL-86-68
## Controlling Backward Inference

**Reference: **
Smith, D. E. Controlling Backward Inference. March, 1987.

**Abstract:** Effective control of inference is a critical problem in Aritificial
Intelligence. Expert systems make use of powerful domain-dependent control
information to eat the combinatorics of inference. However, it is not always
feasible or convenient to provide all of the domain-dependent control that may
be needed, especially for systems that must handle a wide variety of inference
problems, or must function in a changing environment. In this paper, a
powerful domain-independent means of controlling inference is developed. The
basic appproach is to compute expected cost and probability of success for
different backward inference strategies. This information is used to select
between inference steps, and to compute the best oreder for processing
conjunts. The necessary expected cost and probability calculations rely on
simple information about the contents of the problem solver's database, such
as the number of facts of a given form, and the domain sizes for the
predicates and relations involved.

**Notes:** 67 pages.

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