Model Execution in a Goal-Oriented Discrete Event Simulation Environment.

Abstract

Simulation is a powerful technique for the analysis of complex systems. The labor intensive nature of simulation studies, however, shows that current software practices are becoming quickly outmoded with the rising demand for simulation systems. This research addresses an alternate perspective of traditional practices. Simulation is visualized as a problem solving method in which the user specifies the model as well as the analysis goals to be attained by executing the model. Expert software selects the appropriate parameter values that meet analysis goals based on a derived understanding of model behavior. The approach, called goal-oriented simulation, is presented in terms of automated theorem proving. Models are described by rules defining component behavior. Transactions required to verify model behavior are represented as goals. Goals are proven using the specification of model behavior as axioms. Statistics are maintained on the amount of simulated time required to prove each goal. If the inference process does not meet performance criteria given by the user, the cause of poor performance is diagnosed and advice generated as to how to modify model to meet objectives.

Document Details

Document Type
Technical Report
Publication Date
May 01, 1987
Accession Number
ADA176532

Entities

People

  • David A. Umphress

Organizations

  • Air Force Institute of Technology

Tags

DTIC Thesaurus Topics

  • Complex Systems
  • Data Science
  • Environment
  • Information Science
  • Interdisciplinary Science
  • Simulations
  • Specifications
  • Statistics

Fields of Study

  • Computer science
  • Engineering

Readers

  • Regression Analysis.
  • Software Engineering.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference