Dancing With Algorithms: Interaction Creates Greater Preference and Trust in Machine-Learned Behavior

Abstract

We examined a method of machine learning (ML) to evaluate its potential to develop more trustworthy control of unmanned vehicle area search behaviors.

Document Details

• Document Type: Pub Defense Publication
• Publication Date: Feb 12, 2020
• Source ID: 10.1177/0018720820903893

Entities

People

• John Reeder
• Robert S Gutzwiller

Organizations

• Arizona State University
• Naval Information Warfare Center Pacific
• Office of Naval Research
• Office of the Secretary of Defense

Tags

Fields of Study

• Computer science

Readers

• Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
• Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
• Neural Network Machine Learning.

Technology Areas

• AI & ML
• AI & ML - Autonomous Systems
• AI & ML - Neural Networks
• Autonomy
• Autonomy - Human-Robot Interaction