On a Distributed Anytime Architecture for Probabilistic Reasoning.

Abstract

An architecture for unifying various algorithms for probabilistic reasoning is presented. Any algorithms having anytime, anywhere characteristics may be mixed in this scheme. Since algorithms for probabilistic reasoning have widely different behavior over classes of Bayes networks, the scheme permits taking advantage of the set of algorithms that happen to perform well for the problem instance at hand. We concentrate on belief updating and belief revision. Some results are presented for our system (OVERMIND) consisting of several genetic algorithm instances, A*, etc. running in parallel.

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Document Details

Document Type
Technical Report
Publication Date
Apr 21, 1995
Accession Number
ADA293844

Entities

People

  • Edward Williams
  • Eugene Santoe Jr.
  • Solomon E. Shimony

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Bayesian Networks
  • Computations
  • Computer Programming
  • Computer Science
  • Computers
  • Evolutionary Algorithms
  • Genetic Algorithms
  • Integer Programming
  • Linear Programming
  • Optimization
  • Probability
  • Reasoning
  • Simplex Method

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Statistical inference.

Technology Areas

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