Conditions for Implicit Parallelism.

Abstract

Many interesting varieties of genetic algorithms have been designed and implemented in the last fifteen years. One way to improve our understanding of genetic algorithms is to identify properties that are invariant across these seemingly different versions. This paper focuses on invariants among genetic algorithms that differ along two dimensions: the way user-defined objective function is mapped to a fitness measure, and the way the fitness measure is used to assign offspring to parents. A genetic algorithm is called admissible if it meets what seem to be the weakest reasonable requirements along these dimensions. It is shown that any admissible genetic algorithm exhibits a form of implicit parallelism. (AN)

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1995
Accession Number
ADA294110

Entities

People

  • John J. Grefenstette

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Computer Science
  • Computers
  • Convergence
  • Electrical Engineering
  • Electronic Mail
  • Engineering
  • Figure Of Merit
  • Genetic Algorithms
  • Machine Learning
  • Military Research
  • Mutations
  • Psychological Adaptation
  • Sensitivity
  • Theses
  • Universities

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Parallel and Distributed Computing.
  • Theoretical Analysis.

Technology Areas

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