• Corpus ID: 52095196

Deep Emotion: A Computational Model of Emotion Using Deep Neural Networks

  title={Deep Emotion: A Computational Model of Emotion Using Deep Neural Networks},
  author={Chie Hieida and Takato Horii and Takayuki Nagai},
Emotions are very important for human intelligence. [] Key Method The proposed model is implemented using deep neural networks consisting of three modules, which interact with each other. Simulation results reveal that the proposed model exhibits reasonable behavior as the basic mechanism of emotion.
Survey and perspective on social emotions in robotics
It is believed that these higher-level emotions are worth pursuing in robotics for next-generation social-aware robots and research directions towards implementation of social emotions in robots are discussed.
Human Being Emotion in Cognitive Intelligent Robotic Control Pt I: Quantum / Soft Computing Approach
The aim of this part is to demonstrate the possibility of classifying the mental states of a human being operator in on line with knowledge extraction from electroencephalograms based on SCOptKBTM and QCOptKBTM sophisticated toolkit.
An Intelligent Diagnostic System for Evaluating Operator’s Emotions: EEG Processing Toolkit
The article describes a soft computing optimizer of fuzzy controllers that functions as a universal approximator of the training signal operating with the required accuracy and provides deep machine learning.


Emotion Differentiation based on Decision-Making in Emotion Model
A model of emotions is proposed based on various neurological and psychological findings related to empathic communication between humans and robots and a decision-making mechanism based on affects using convolutional long short-term memory and deep deterministic policy gradient is examined.
Decision-Making in Emotion Model
A model of emotions based on various neurological and psychological findings that are related to empathic communication between humans and robots is proposed and a mechanism of decision-making that is based on affects using convolutional LSTM and deep Q-network is examined.
Emotion in reinforcement learning agents and robots: a survey
This article provides the first survey of computational models of emotion in reinforcement learning (RL) agents, and systematically addresses from what underlying dimensions emotions can be derived and how these can be modelled in RL-agents.
The quartet theory of human emotions: An integrative and neurofunctional model.
A Model of Emotion for Empathic Communication
A model of emotion based on some neurological and psychological findings concerning empathic communication between humans and robots is proposed, and a method for generating affect for given visual stimuli using a recurrent neural network as a first step is examined.
Robotic emotional model with personality factors based on Pleasant-Arousal scaling model
  • Naoki Masuyama, C. Loo
  • Psychology
    2015 24th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN)
  • 2015
Three stages (core affects, emotion and mood) robotic emotional model with OCEAN model as the personality factors based on 2D (Pleasant-Arousal) scaling model are proposed and the results from simulation experiment show that the proposed model is able to generate the different emotional properties based on the Personality factors.
A Recipe for Empathy
This is the first emotion system to recognize adult emotional voices after training only with motherese, suggesting that this specific parental behavior may help build emotional intelligence.
Robot personality based on the equations of emotion defined in the 3D mental space
A robot personality is proposed which consists of sensing personality and expression personality which has the ability to communicate naturally with a human by expressing human-like emotion.
Cognitive-Emotional Interactions in the Brain
Emotional experiences, it is proposed, result when stimulus representations, affect representations, and self representations coincide in working memory.
Verbal conversation system for a socially embedded robot partner using emotional model
This paper proposes a verbal conversation system for a robot partner using emotional model, which uses emotional parameters based on the human sentences to make a natural communication system.