A hierarchical emotion regulated sensorimotor model: Case studies

Junpei Zhong, Rony Novianto, Mingjun Dai, Xinzheng Zhang, Angelo Cangelosi

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

5 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationProceedings of the 28th Chinese Control and Decision Conference, CCDC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4965-4970
Number of pages6
ISBN (Electronic)9781467397148
DOIs
Publication statusPublished - 3 Aug 2016
Externally publishedYes
Event28th Chinese Control and Decision Conference, CCDC 2016 - Yinchuan, China
Duration: 28 May 201630 May 2016

Publication series

NameProceedings of the 28th Chinese Control and Decision Conference, CCDC 2016

Conference

Conference28th Chinese Control and Decision Conference, CCDC 2016
Country/TerritoryChina
CityYinchuan
Period28/05/1630/05/16

Keywords

  • Cognitive Architecture
  • Embodied Emotion Modelling
  • Non-verbal Emotion Expression
  • Recurrent Neural Networks
  • Social Robotics

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Control and Optimization
  • Statistics, Probability and Uncertainty
  • Artificial Intelligence
  • Decision Sciences (miscellaneous)

Cite this