Modelling Machine Emotions for Realizing Intelligence: Foundations and Applications
Toyoaki Nishida, Colette Faucher
Springer Science & Business Media, Jun 21, 2010 - Mathematics - 228 pages
Emotion connects the thought to the body, which is a magnificent biological - vice for sensing and affecting the world. The thought controls the body through emotions. The body affects the thought through emotions. Through this mec- nism, the thought allows the agent to behave intelligently in the complex world filled with a huge amount of dynamic information. The emotion maps a flux of information into a space which the agent is familiar with, enabling her/him to associate ongoing events with past experiences which help to reduce complexity by providing with a nominal solution. Recent findings in brain science suggest that mirror neurons map visual signals into motor signals for the body. This mechanism might permit one to experience the emotion of the other agent just by feeling the motor signals caused by mirror neurons as a result of visual stimuli caused by the other agent’s emotional beh- iors. In particular, it might play a significant role in invoking empathy in a social situation. It may not be hard to think about what might happen to emotion-less machines. The emotion-less machines may not be able to accumulate experiences to avoid serious failures. They may not be able to communicate with the humans in an empathetic way.
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Modelling Machine Emotions for Realizing Intelligence: Foundations and ...
Toyoaki Nishida,Colette Faucher
No preview available - 2012
A-condition activation Affect Analysis Model AffectIM algorithm annotations approach architecture atmosphere of I-measure automatic basic emotions behavior chapter cognitive communication component Computational Intelligence contrast effects detect I-measure dynamics ECAs embodied conversational agents EmoHeart emoticons emotion engine emotional facial expression emotional intelligence emotional model engineer environment episodic memory evaluation example experiment facial animation facial expression synthesis feelings framework function gaze controller habituation Heidelberg human I-measure implemented Implicit Association Test input interaction protocol interface layer learning machine learning mechanism mental method mirror neurons module mood neural neuron Nishida nonverbal participants partner robots perceptual person physiological indices Prendinger prime duration processes proposed questionnaire quiz game recognition reinforcement learning represent response role secondary emotions sentences shows simulation social social robots speech stimulus subsumption architecture talking avatar target theory threshold tion updated users valence virtual characters viseme visual information words