Emotion Generation System based on MaC Model with Neural Networks

Abstract

In this paper, we propose an emotion generation system based on MaC model using neural networks. In the proposed system, the chaotic neural network and the Boltzmann machine are used in the Emotion Generator of the MaC model. In the Boltzmann machine, the plural pattern can be recalled stochastically for the same input. The proposed system makes use of this property in order to generate different emotions for same external input. On the other hand, the chaotic neural network can recall the training patterns dynamically based on external input and the history. The proposed system makes use of this property in order to generate emotions based on its history. We carried out computer experiments, and confirmed that the proposed system can realize autonomous and human-like emotion generation. Moreover, we confirmed that the robot based on the proposed system can decide actions as similar as in the robot operated manually.