A Toolkit for Building Hybrid, Multi-Resolution PMESII Models

Abstract

A software toolkit for constructing, integrating, debugging, validating and verifying, and maintaining heterogeneous Political, Military, Economic, Social Information, and Infrastructure (PMESII) models in support of a Commander's Predictive Environment (CPE) was developed. This development environment is based upon Charles River Analytic's Graphical Agent Development Environment (GRADE), and provides intuitive graphical tools supporting the development of new models and adaptation of existing PMESII models. The component-based software architecture enables the injection of new modeling paradigms, e.g., semantic networks, system dynamic models, etc., and existing legacy PMESII models; as well as GUI-based model tools to enable data-level integration. The toolkit provides (1) an intuitive graphical model development environment, (2) a suite of model integration tools, (3) a suite of model verification and validation tools, (4) a model analysis infrastructure, (5) a suite of multi-resolution modeling tools and supporting infrastructure, and (6) a model management infrastructure.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2007
Accession Number
ADA475418

Entities

People

  • John Bachman
  • Karen A. Harper

Tags

Communities of Interest

  • C4I
  • Engineered Resilient Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Bayesian Networks
  • Computational Science
  • Debugging
  • Graphical User Interface
  • Information Processing
  • Information Retrieval
  • Information Science
  • Information Systems
  • Neural Networks
  • Ontologies
  • Probability
  • Psychology
  • Reasoning
  • Software Design
  • Software Development
  • Software Testing

Fields of Study

  • Computer science
  • Engineering

Readers

  • Computational Modeling and Simulation
  • Database Systems and Applications
  • Irregular Warfare and Special Operations Cyberspace Operations against Adversarial Threats.