Detection and Learning of Unexpected Behaviors of Systems of Dynamical Systems by Using the Q2 Abstractions

Abstract

This report describes the research on characterization and detection of emergent behaviors in groups of dynamical systems (agents) performing a common mission. The mission was related to monitoring of plume. The main objective of this research was the reduction of the complexity of emergence detection through the use of the theory of similitude and of qualitative abstractions of dynamical systems.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 2017
Accession Number
AD1041621

Entities

People

  • Mitch Kokar
  • Shan Lu
  • Shweta Singh

Organizations

  • Northeastern University

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Algorithms
  • Complex Adaptive Systems
  • Complex Systems
  • Computational Science
  • Computer Languages
  • Control Systems
  • Information Science
  • Information Systems
  • Machine Learning
  • Mathematical Models
  • Multiagent Systems
  • Ontologies
  • Self Organizing Systems
  • Two Dimensional
  • Unmanned Aerial Vehicles

Readers

  • Neural Network Machine Learning.
  • Theoretical Analysis.