TY - GEN
T1 - A hierarchical emotion regulated sensorimotor model
T2 - 28th Chinese Control and Decision Conference, CCDC 2016
AU - Zhong, Junpei
AU - Novianto, Rony
AU - Dai, Mingjun
AU - Zhang, Xinzheng
AU - Cangelosi, Angelo
N1 - Funding Information:
JZ and AC were supported by the EU project POETICON++ under grant agreement 288382 and UK EPSRC project BABEL. MD was supported by NSF of China (61301182), NSF of Guangdong (S2013040016857), Specialized Research Fund for the Doctoral Program of Higher Education from the Ministry of Education (20134408120004), Yumiao Engineering from Education Department of Guangdong (2013LYM 0077), Foundation of Shenzhen City (KQCX20140509172609163), and from NSF of Shenzhen University (00002501, 00036107). JZ would like to acknowledge the data-set and inspirations from L. Canamero and M. Lewis from University of Hertfordshire
Publisher Copyright:
© 2016 IEEE.
PY - 2016/8/3
Y1 - 2016/8/3
N2 - Inspired by the hierarchical cognitive architecture and the perception-action model (PAM) [14], we propose that the internal status acts as a kind of common-coding representation which affects, mediates and even regulates the sensorimotor behaviours. These regulation can be depicted in the Bayesian framework, that is why cognitive agents are able to generate behaviours with subtle differences according to their emotion or recognize the emotion by perception. A novel recurrent neural network called recurrent neural network with parametric bias units (RNNPB) runs in three modes, constructing a two-level emotion regulated learning model, was further applied to testify this theory in two different cases.
AB - Inspired by the hierarchical cognitive architecture and the perception-action model (PAM) [14], we propose that the internal status acts as a kind of common-coding representation which affects, mediates and even regulates the sensorimotor behaviours. These regulation can be depicted in the Bayesian framework, that is why cognitive agents are able to generate behaviours with subtle differences according to their emotion or recognize the emotion by perception. A novel recurrent neural network called recurrent neural network with parametric bias units (RNNPB) runs in three modes, constructing a two-level emotion regulated learning model, was further applied to testify this theory in two different cases.
KW - Cognitive Architecture
KW - Embodied Emotion Modelling
KW - Non-verbal Emotion Expression
KW - Recurrent Neural Networks
KW - Social Robotics
UR - https://www.scopus.com/pages/publications/84983781013
U2 - 10.1109/CCDC.2016.7531882
DO - 10.1109/CCDC.2016.7531882
M3 - Conference article published in proceeding or book
AN - SCOPUS:84983781013
T3 - Proceedings of the 28th Chinese Control and Decision Conference, CCDC 2016
SP - 4965
EP - 4970
BT - Proceedings of the 28th Chinese Control and Decision Conference, CCDC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 28 May 2016 through 30 May 2016
ER -