Tractable Inference Relations

Abstract

This paper considers the concept of local sets of inference rules. Locality is a syntactic condition on rule sets which guarantees that the inference relation defined by those rules is polynomial time decidable. Unfortunately, determining whether a given rule set is local can be difficult. In this paper, the authors define inductive locality, a strengthening of locality. They also give a procedure which can automatically recognize the locality of any inductively local rule set. Inductive locality seems to be more useful that the earlier concept of strong locality. There are many natural examples of inductively local rule sets that are not strongly local. They have not found any natural examples of local rule sets that fail to be inductively local. However, they show here that locality, as a property of rule sets, is undecidable in general.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1991
Accession Number
ADA260169

Entities

People

  • David Mcallester
  • Robert Givan

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Artificial Intelligence Computing
  • Automata
  • Availability
  • Computations
  • Computer Programming
  • Guarantees
  • Language
  • Massachusetts
  • Mathematics
  • Military Research
  • Polynomials
  • Reasoning
  • Sequences
  • Standards
  • Trees (Data Structures)

Fields of Study

  • Economics

Readers

  • Artificial Intelligence
  • Mathematical Modeling and Probability Theory.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • AI & ML - Machine Translation