Accession Number:

ADA616513

Title:

How Much Do You Trust Me? Learning a Case-Based Model of Inverse Trust

Descriptive Note:

Conference paper

Corporate Author:

NAVAL RESEARCH LAB WASHINGTON DC NAVY CENTER FOR APPLIED RESEARCH IN ARTIFICIAL INTELLIGENCE

Report Date:

2014-10-01

Pagination or Media Count:

16.0

Abstract:

Robots can be important additions to human teams if they improve team performance by providing new skills or improving existing skills. However, to get the full benefits of a robot the team must trust and use it appropriately. We present an agent algorithm that allows a robot to estimate its trustworthiness and adapt its behavior in an attempt to increase trust. It uses case-based reasoning to store previous behavior adaptations and uses this information to perform future adaptations. We compare case-based behavior adaptation to behavior adaptation that does not learn and show it significantly reduces the number of behaviors that need to be evaluated before a trustworthy behavior is found. Our evaluation is in a simulated robotics environment and involves a movement scenario and a patrollingthreat detection scenario.

Subject Categories:

  • Cybernetics
  • Human Factors Engineering and Man Machine Systems

Distribution Statement:

APPROVED FOR PUBLIC RELEASE