The Avocado Paper: A Path Toward Ontology-based Predictive Models for HumanAutonomous Teaming

Abstract

The purpose of this report is to support one of four Human Autonomous Teaming (HAT) Essential Research Program research areas that entails development of predictive models to evaluate HAT interaction. Predictive models would enable researchers to weigh the merits of a course of action pursuant to a given scenario or contingency in question, then apply time and resources to that action based on the strength of the model outcome. It is posited that an ontology framework could be developed to horizontally integrate data that are vertically defined within taxonomies. The data would then be directed to a data analytics module to evaluate HAT scenarios.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Feb 04, 2020
Accession Number
AD1090979

Entities

People

  • Paul Shorter

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Commerce
  • Data Analysis
  • Data Integration
  • Data Mining
  • Data Science
  • Decision Support Systems
  • Engineering
  • Information Science
  • Information Systems
  • Machine Learning
  • Management Information Systems
  • Models
  • Ontologies
  • Predictive Modeling
  • Simulations
  • Taxonomy

Readers

  • Distributed Systems and Data Platform Development
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.
  • Wave Propagation and Nonlinear Chaotic Dynamics.