On Some Issues Concerning Optimization and Decision Trees.

Abstract

The authors describe the context and the constituent modules of a large-scale programming system, the Quasi-Optimizer. Its objectives are (a) to observe and measure adversaries' behavior in a competitive environment, to infer their strategies and to construct a computer model, a descriptive theory of each; (b) to identify strategy components, evaluate their effectiveness and to select the most satisfactory ones from a set of descriptive theories; (c) to combine these components in a quasi-optimum strategy that represents a normative theory in the statistical sense. Also discussed are certain properties of decision trees which are the primary representational structures of strategies in the computer. The verification of these properties, such as identity, equivalence and similarity between two decision subtrees, enable us to eliminate redundancies in the decision trees.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1983
Accession Number
ADA134109

Entities

People

  • Michael S. Belofsky
  • Nicholas V. Findler
  • Timothy W. Bickmore

Organizations

  • Arizona State University

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Abstracts
  • Artificial Intelligence
  • Classification
  • Computer Programming
  • Computer Science
  • Computers
  • Environment
  • Experimental Design
  • Identities
  • Learning
  • Optimization
  • Pattern Recognition
  • Probability Distributions
  • Redundancy
  • Security
  • Universities
  • Verification

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computational Linguistics
  • Strategic Security Studies

Technology Areas

  • AI & ML