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


Personal Author(s) : Floyd, Michael W ; Drinkwater, Michael ; Aha, David W


Full Text : http://www.dtic.mil/dtic/tr/fulltext/u2/a616513.pdf


Report Date : Oct 2014


Pagination or Media Count : 16


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 patrolling/threat detection scenario.


Descriptors :   *ADAPTATION , *BEHAVIOR , *ROBOTS , ALGORITHMS , CASE STUDIES , DETECTION , ENVIRONMENTS , LEARNING , PATROLLING , PERFORMANCE(HUMAN) , ROBOTICS , SCENARIOS , SIMULATION , SKILLS , TEAMS(PERSONNEL) , THREATS


Subject Categories : Cybernetics
      Human Factors Engineering & Man Machine System


Distribution Statement : APPROVED FOR PUBLIC RELEASE