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Decision-Making in Emotion Model

Authors:

Chie Hieida,

Takato Horii,

Takayuki NagaiAuthors Info & Claims

HRI '18: Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction

Pages 127 - 128

https://doi.org/10.1145/3173386.3177048

Published: 01 March 2018 Publication History

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Abstract

Having emotions is essential for robots to understand and sympathize with the feelings of people. In addition, it may allow the robots to be accepted into human society. The role of emotions in decision-making is another important perspective. In this paper, a model of emotions based on various neurological and psychological findings that are related to empathic communication between humans and robots is proposed. Subsequently, a mechanism of decision-making that is based on affects using convolutional LSTM and deep Q-network is examined.

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Cited By

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Assuncao GPatrao BCastelo-Branco MMenezes P(2022)An Overview of Emotion in Artificial IntelligenceIEEE Transactions on Artificial Intelligence10.1109/TAI.2022.31596143:6(867-886)Online publication date: Dec-2022
https://doi.org/10.1109/TAI.2022.3159614
Hung PIqbal FAleem SRafferty L(2021)Snapshot of Research Issues in Service RobotsService-Oriented Computing – ICSOC 2021 Workshops10.1007/978-3-031-14135-5_32(363-376)Online publication date: 22-Nov-2021
https://dl.acm.org/doi/10.1007/978-3-031-14135-5_32
Harata SSakuma TKato STruong KHeylen DCzerwinski MBerthouze NChetouani MNakano M(2020)Toward Mathematical Representation of Emotion: A Deep Multitask Learning Method Based On Multimodal RecognitionCompanion Publication of the 2020 International Conference on Multimodal Interaction10.1145/3395035.3425254(47-51)Online publication date: 25-Oct-2020
https://dl.acm.org/doi/10.1145/3395035.3425254
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Index Terms

Decision-Making in Emotion Model
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
      1. Cognitive robotics

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Published In

HRI '18: Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction

March 2018

431 pages

ISBN:9781450356152

DOI:10.1145/3173386

General Chairs:
Takayuki Kanda
ATR, Japan
,
Selma Ŝabanović
Indiana University Bloomington, USA
,
Program Chairs:
Guy Hoffman
Cornell University, USA
,
Adriana Tapus
ENSTA-ParisTech, France

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 March 2018

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Core Research for Evolutional Science and Technology
Ministry of Education, Culture, Sports, Science and Technology
Japan Society for the Promotion of Science
Japan Science and Technology Agency

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HRI '18

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SIGAI
SIGCHI
IEEE-RAS

HRI '18: ACM/IEEE International Conference on Human-Robot Interaction

March 5 - 8, 2018

IL, Chicago, USA

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HRI '18 Paper Acceptance Rate 49 of 206 submissions, 24%;

Overall Acceptance Rate 192 of 519 submissions, 37%

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Assuncao GPatrao BCastelo-Branco MMenezes P(2022)An Overview of Emotion in Artificial IntelligenceIEEE Transactions on Artificial Intelligence10.1109/TAI.2022.31596143:6(867-886)Online publication date: Dec-2022
https://doi.org/10.1109/TAI.2022.3159614
Hung PIqbal FAleem SRafferty L(2021)Snapshot of Research Issues in Service RobotsService-Oriented Computing – ICSOC 2021 Workshops10.1007/978-3-031-14135-5_32(363-376)Online publication date: 22-Nov-2021
https://dl.acm.org/doi/10.1007/978-3-031-14135-5_32
Harata SSakuma TKato STruong KHeylen DCzerwinski MBerthouze NChetouani MNakano M(2020)Toward Mathematical Representation of Emotion: A Deep Multitask Learning Method Based On Multimodal RecognitionCompanion Publication of the 2020 International Conference on Multimodal Interaction10.1145/3395035.3425254(47-51)Online publication date: 25-Oct-2020
https://dl.acm.org/doi/10.1145/3395035.3425254
Maroto-Gómez MCastro-González ÁCastillo JMalfaz MSalichs M(2018)A Bio-inspired Motivational Decision Making System for Social Robots Based on the Perception of the UserSensors10.3390/s1808269118:8(2691)Online publication date: 16-Aug-2018
https://doi.org/10.3390/s18082691
Hieida CHorii TNagai T(2018)Emotion Differentiation based on Decision-Making in Emotion Model2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN)10.1109/ROMAN.2018.8525579(659-665)Online publication date: 27-Aug-2018
https://dl.acm.org/doi/10.1109/ROMAN.2018.8525579
Hieida CHorii TNagai T(2018)Toward Empathic Communication: Emotion Differentiation via Face-to-Face Interaction in Generative Model of Emotion2018 Joint IEEE 8th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob)10.1109/DEVLRN.2018.8761026(66-71)Online publication date: Sep-2018
https://doi.org/10.1109/DEVLRN.2018.8761026

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A Model of Emotion for Empathic Communication

Bayesian model of the social effects of emotion in decision-making in multiagent systems

Development of an Emotion-Competent SLAM Agent

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A Model of Emotion for Empathic Communication

Bayesian model of the social effects of emotion in decision-making in multiagent systems

Development of an Emotion-Competent SLAM Agent

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