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A game theoretic queueing approach to self-assessment in human-robot interaction systems

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3 Author(s)
Tinglong Dai ; Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA ; Katia Sycara ; Michael Lewis

This paper presents a queueing model that ad dresses robot self-assessment in human-robot-interaction systems. We build the model based on a game theoretic queueing approach, and analyze four issues: 1) individual differences in operator skills/capabilities, 2) differences in difficulty of presenting tasks, 3) trade-off between human interaction and performance and 4) the impact of task heterogeneity in the optimal service decision-making and system performance. The subsequent analytical and numerical exploration helps under stand the way the decentralized decision-making scheme is affected by various service environments.

Published in:

Robotics and Automation (ICRA), 2011 IEEE International Conference on

Date of Conference:

9-13 May 2011