A Probabilistic Model for Uncertain Problem Solving

Abstract

With growing interest in the application of research to problems that arise in real-world contexts, issues raised by consideration of uncertain states and unreliable operators are receiving increased attention in artificial intelligence research. In this paper, a model is presented for dealing with such concerns. The model is a probabilistic generalization of the familiar notion of "problem space." The author discusses the specification of uncertain states and unreliable operators, problem-solving search methods, and the need for information-gathering operators to control state disunity and provide pragmatic focusing. Search methods are generalized to produce tree-structured plans incorporating the use of such operators. Several application domains for the model also are discussed.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1981
Accession Number
ADA458836

Entities

People

  • Arthur M. Farley

Organizations

  • SRI International

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Applied Computer Science
  • Artificial Intelligence
  • Artificial Intelligence Computing
  • Artificial Intelligence Software
  • Availability
  • Classification
  • Computer Science
  • Contracts
  • Information Operations
  • Instructions
  • Machine Learning
  • Models
  • Probabilistic Models
  • Specifications
  • Standards

Readers

  • Artificial Intelligence
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • AI & ML - Machine Learning Algorithms
  • Space