@inproceedings{7ce23ecc113c4e429de2f86f0d114832,
title = "Analysis of an intention-response model inspired by brain nervous system for cognitive robot",
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.",
author = "Yu, {Jae Min} and Cho, {Sung Bae}",
year = "2016",
month = jan,
day = "1",
doi = "10.1007/978-3-319-46687-3_18",
language = "English",
isbn = "9783319466866",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "168--176",
editor = "Kenji Doya and Kazushi Ikeda and Minho Lee and Akira Hirose and Seiichi Ozawa and Derong Liu",
booktitle = "Neural Information Processing - 23rd International Conference, ICONIP 2016, Proceedings",
address = "Germany",
note = "23rd International Conference on Neural Information Processing, ICONIP 2016 ; Conference date: 16-10-2016 Through 21-10-2016",
}