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Predicting trust in human control of swarms via inverse reinforcement learning

Nam, Changjoo and Walker, Phillip and Lewis, Michael and Sycara, Katia (2018) Predicting trust in human control of swarms via inverse reinforcement learning. In: 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), 27-31 Aug 2018, Lisbon, Portugal.

Abstract

In this paper, we study the model of human trust where an operator controls a robotic swarm remotely for a search mission. Existing trust models in human-in- the-loop systems are based on task performance of robots. However, we find that humans tend to make their decisions based on physical characteristics of the swarm rather than its performance since task performance of swarms is not clearly perceivable by humans. We formulate trust as a Markov decision process whose state space includes physical parameters of the swarm. We employ an inverse reinforcement learning algorithm to learn behaviors of the operator from a single demonstration. The learned behaviors are used to predict the trust level of the operator based on the features of the swarm.


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Details

Item Type: Conference or Workshop Item (Paper)
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Nam, Changjoo
Walker, Phillip
Lewis, Michaelml@sis.pitt.educmlewis0000-0002-1013-9482
Sycara, Katia
Date: 2018
Date Type: Publication
Journal or Publication Title: 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN)
Page Range: pp. 528-533
Event Title: 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN)
Event Dates: 27-31 Aug 2018
Event Type: Conference
Schools and Programs: School of Computing and Information > Information Science
Refereed: Yes
Date Deposited: 06 Jul 2018 15:57
Last Modified: 06 Jul 2018 15:57
URI: http://d-scholarship.pitt.edu/id/eprint/34586

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