Active Behavior Recognition in Beyond Visual Range Air Combat

Abstract

Accurately modeling uncontrolled agents (or recognizing their behavior and intentions) is critical to planning and acting in a multi-agent environment. However, behavior recognition systems are only as good as their observations. Here we argue that acting, even acting at random, can be a critical part of gathering those observations. Furthermore, we claim that acting intelligently via automated planning can significantly reduce the time it takes to confidently classify agent behaviors. We present a formalism and algorithm for integrated planning and recognition, as well as its implementation in a beyond visual range air combat simulator. We found that it yields better behavior recognition than non-integrated approaches. This provides evidence that behavior recognition is not just a necessary component of an intelligent agent, but that good behavior recognition requires intelligent acting.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 2015
Accession Number
ADA626583

Entities

People

  • David W. Aha
  • Hayley Borck
  • Justin Karneeb
  • Ron Alford

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Counter WMD
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Artificial Intelligence
  • Environment
  • Information Processing
  • Information Science
  • Information Systems
  • Intelligent Agents
  • Military Research
  • Multiagent Systems
  • Observation
  • Probability
  • Probability Distributions
  • Recognition
  • Simulations
  • Simulators
  • Unmanned Aerial Vehicles

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Distributed Systems and Data Platform Development
  • Strategic Security Studies