Analysis of an intention-response model inspired by brain nervous system for cognitive robot

Jae Min Yu; Sung Bae Cho

doi:10.1007/978-3-319-46687-3_18

Analysis of an intention-response model inspired by brain nervous system for cognitive robot

Jae Min Yu, Sung Bae Cho

College of Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

A service robot requires natural and interactive interaction with users without explicit commands. It is still one of the difficult problems to generate robust reactions for the robot in the real environment with unreliable sensor data to satisfy user’s requests. This paper presents an intention-response model based on mirror neuron and theory of mind, and analyzes the performance for a humanoid to show the usefulness. The model utilizes the modules of behavior selection networks to realize prompt response and goal-oriented characteristics of the mirror neuron, and performs reactions according to an action plan based on theory of mind. To cope with conflicting goals, behaviors of the sub-goal unit are generated using a hierarchical task network. Experiments with various scenarios reveal that appropriate reactions are generated according to external stimuli.

Original language	English
Title of host publication	Neural Information Processing - 23rd International Conference, ICONIP 2016, Proceedings
Editors	Kenji Doya, Kazushi Ikeda, Minho Lee, Akira Hirose, Seiichi Ozawa, Derong Liu
Publisher	Springer Verlag
Pages	168-176
Number of pages	9
ISBN (Print)	9783319466866
DOIs	https://doi.org/10.1007/978-3-319-46687-3_18
Publication status	Published - 2016
Event	23rd International Conference on Neural Information Processing, ICONIP 2016 - Kyoto, Japan Duration: 2016 Oct 16 → 2016 Oct 21

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9947 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	23rd International Conference on Neural Information Processing, ICONIP 2016
Country/Territory	Japan
City	Kyoto
Period	16/10/16 → 16/10/21

Bibliographical note

Funding Information:
This work was supported by the Industrial strategic technology development program, 10044828, Development of augmenting multisensory technology for enhancing significant effect on service industry funded by the Ministry of Trade, industry & Energy (MI, Korea).

Publisher Copyright:
© Springer International Publishing AG 2016.

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-319-46687-3_18

Cite this

Yu, J. M., & Cho, S. B. (2016). Analysis of an intention-response model inspired by brain nervous system for cognitive robot. In K. Doya, K. Ikeda, M. Lee, A. Hirose, S. Ozawa, & D. Liu (Eds.), Neural Information Processing - 23rd International Conference, ICONIP 2016, Proceedings (pp. 168-176). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9947 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-46687-3_18

Yu, Jae Min ; Cho, Sung Bae. / Analysis of an intention-response model inspired by brain nervous system for cognitive robot. Neural Information Processing - 23rd International Conference, ICONIP 2016, Proceedings. editor / Kenji Doya ; Kazushi Ikeda ; Minho Lee ; Akira Hirose ; Seiichi Ozawa ; Derong Liu. Springer Verlag, 2016. pp. 168-176 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "A service robot requires natural and interactive interaction with users without explicit commands. It is still one of the difficult problems to generate robust reactions for the robot in the real environment with unreliable sensor data to satisfy user{\textquoteright}s requests. This paper presents an intention-response model based on mirror neuron and theory of mind, and analyzes the performance for a humanoid to show the usefulness. The model utilizes the modules of behavior selection networks to realize prompt response and goal-oriented characteristics of the mirror neuron, and performs reactions according to an action plan based on theory of mind. To cope with conflicting goals, behaviors of the sub-goal unit are generated using a hierarchical task network. Experiments with various scenarios reveal that appropriate reactions are generated according to external stimuli.",

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Yu, JM & Cho, SB 2016, Analysis of an intention-response model inspired by brain nervous system for cognitive robot. in K Doya, K Ikeda, M Lee, A Hirose, S Ozawa & D Liu (eds), Neural Information Processing - 23rd International Conference, ICONIP 2016, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9947 LNCS, Springer Verlag, pp. 168-176, 23rd International Conference on Neural Information Processing, ICONIP 2016, Kyoto, Japan, 16/10/16. https://doi.org/10.1007/978-3-319-46687-3_18

Analysis of an intention-response model inspired by brain nervous system for cognitive robot. / Yu, Jae Min; Cho, Sung Bae.

Neural Information Processing - 23rd International Conference, ICONIP 2016, Proceedings. ed. / Kenji Doya; Kazushi Ikeda; Minho Lee; Akira Hirose; Seiichi Ozawa; Derong Liu. Springer Verlag, 2016. p. 168-176 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9947 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - A service robot requires natural and interactive interaction with users without explicit commands. It is still one of the difficult problems to generate robust reactions for the robot in the real environment with unreliable sensor data to satisfy user’s requests. This paper presents an intention-response model based on mirror neuron and theory of mind, and analyzes the performance for a humanoid to show the usefulness. The model utilizes the modules of behavior selection networks to realize prompt response and goal-oriented characteristics of the mirror neuron, and performs reactions according to an action plan based on theory of mind. To cope with conflicting goals, behaviors of the sub-goal unit are generated using a hierarchical task network. Experiments with various scenarios reveal that appropriate reactions are generated according to external stimuli.

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Yu JM, Cho SB. Analysis of an intention-response model inspired by brain nervous system for cognitive robot. In Doya K, Ikeda K, Lee M, Hirose A, Ozawa S, Liu D, editors, Neural Information Processing - 23rd International Conference, ICONIP 2016, Proceedings. Springer Verlag. 2016. p. 168-176. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-46687-3_18

Analysis of an intention-response model inspired by brain nervous system for cognitive robot

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