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Spiking neural network based emotional model for robot partner

János Botzheim, Naoyuki Kubota

Year
2014
Citations
8

Abstract

In this paper, a spiking neural network based emotional model is proposed for a smart phone based robot partner. Since smart phone has limited computational power compared to personal computers, a simple spike response model is applied for the neurons in the neural network. The network has three layers following the concept of emotion, feeling, and mood. The perceptual input stimulates the neurons in the first, emotion layer. Weights adjustment is also proposed for the interconnected neurons in the feeling layer and between the feeling and mood layer based on Hebbian learning. Experiments are presented to validate the proposed method. Based on the emotional model, the output action such as gestural and facial expressions for the robot is calculated.

Keywords

Hebbian theoryComputer scienceSpiking neural networkFeelingArtificial neural networkRobotMoodLayer (electronics)Boltzmann machineArtificial intelligence

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