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Reconstructing Gene Networks of Forest Trees from Gene Expression Data: Toward Higher-Resolution Approaches Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Emotion-Aware Teaching Robot: Learning to Adjust to User’s Emotional State

Authors : Frosina Stojanovska, Martina Toshevska, Vesna Kirandziska, Nevena Ackovska

Published in: ICT Innovations 2018. Engineering and Life Sciences

Publisher: Springer International Publishing

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Abstract

Robots today are taking more and more complex roles thus they are getting smarter and more human-like. One complex function, specific to social robots, is the role of robots in human-robot interaction. They are helpful in the process of social human-robot interaction while performing a specific task like teaching, assisting, entertaining, etc. The ability to recognize emotions has a significant role for social robots. A robot that can understand emotions could be able to interact according to that emotion. In this paper, we propose a model for robotic behavior adapting to the user’s emotions. The humanoid robot Nao is used in the role of emotion-aware teacher for teaching math. Its main purpose is to teach and entertain the user while adapting its behavior to the user’s emotional state derived from the facial expression. The robot uses reinforcement learning to learn which action to perform in a specific emotional state. It employs the Q-learning algorithm, maximizing the next action’s award - a value that depends on the current emotional state of the user. An experimental study with a selected group of subjects is conducted to assess the proposed behavior. We evaluated the robot’s ability to recognize emotions and the subjects’ experience of interacting with the robot.

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Metadata
Title
Emotion-Aware Teaching Robot: Learning to Adjust to User’s Emotional State
Authors
Frosina Stojanovska
Martina Toshevska
Vesna Kirandziska
Nevena Ackovska
Copyright Year
2018
Book
ICT Innovations 2018. Engineering and Life Sciences

Print ISBN: 978-3-030-00824-6

Electronic ISBN: 978-3-030-00825-3

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-030-00825-3_6

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