Artificial Intelligence through Evolutionary Programming: Prediction and Identification

Abstract

This report examines the manner by which evolutionary programming treats an arbitrary prediction problem. Additional experiments were conducted to clarify uncertainties given increased machine size and the cost/benefit of retaining offspring programs, the impact of noise on the predictive capability of the evolutionary process, and the efficacy of crossover as a mechanism for improving simulated evolution. It was also found that some difficult combinatorial problems such as the classic Traveling Salesman Problem can be addressed through less complex logics.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1986
Accession Number
ADA171544

Entities

People

  • David Fogel
  • Lawrence J. Fogel

Organizations

  • Titan Corp.

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies
  • Weapons Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Alphabets
  • Artificial Intelligence
  • Chromosomes
  • Climate Change
  • Computations
  • Computer Programming
  • Computers
  • Confidence Limits
  • Data Science
  • Environment
  • Genetic Algorithms
  • Genetics
  • Parallel Computing
  • Parallel Processing
  • Plastic Explosives
  • Social Sciences

Readers

  • Computational Modeling and Simulation
  • Operations Research
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - DoD AI Strategy
  • AI & ML - Machine Learning Algorithms
  • AI & ML - Neural Networks