Optics and Symbolic Computing

Abstract

Many problems in Artificial Intelligence are intractable due to the exponential growth of the solution space with problem size. Often these problems can benefit from heuristic search or forward-checking techniques which attempt to prune the search space down to a manageable size before or during the actual search procedure. Many interesting search problems can be formulated as consistent labeling problem in which initial problem information is given in the form of a set of binary constraint, for which Boolean matrices are a natural data representation. In this paper optical implementations of Boolean matrix operations are proposed for manipulating the constraint matrices to perform forward-checking and thereby increase the search efficiency. The high degree of parallelism afforded by using optical techniques and the relatively low accuracy requirements of Boolean matrix operations suggest that optical techniques are well matched to this problem.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1988
Accession Number
ADA200564

Entities

People

  • Athale

Organizations

  • Braddock Dunn & McDonald

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Artificial Intelligence
  • Circuit Boards
  • Computations
  • Computer Architecture
  • Computers
  • Computing System Architectures
  • Corporations
  • Detection
  • Optical Interconnects
  • Parallel Computing
  • Parallel Processing
  • Parallel Processors
  • Scientific Research
  • Three Dimensional
  • Trees (Data Structures)
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Operations Research

Technology Areas

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