A Framework for Evidence-Based Licensure of Adaptive Autonomous Systems: Technical Areas

Abstract

Adaptive autonomous systems of interest to DoD have great potential to complement human performance in a wide range of missions. This particularly is true for adaptive systems that learn those whose behavior on a given set of inputs may change over time, even after the system has been fielded. However, such adaptation makes exhaustive testing, certification, and licensure of the final system impossible.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2016
Accession Number
AD1020297

Entities

People

  • Christopher A. Martin
  • David A. Sparrow
  • David M. Tate
  • Franklin L. Moses
  • Rebecca A. Grier

Organizations

  • Institute for Defense Analyses

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Adaptive Systems
  • Air Force
  • Aircrafts
  • Artificial Intelligence
  • Autonomous Systems
  • Cognitive Systems Engineering
  • Computer Programming
  • Computers
  • Human-Machine Systems
  • Performance Tests
  • Probabilistic Models
  • Situational Awareness
  • Systems Engineering
  • Test And Evaluation
  • Unmanned Aerial Vehicles
  • Unmanned Systems
  • Unmanned Vehicles

Readers

  • Medical or Health Care Field.
  • Robotics and Automation.
  • Systems Analysis and Design

Technology Areas

  • Autonomy
  • Autonomy - Autonomous System Control