Abstract : This paper proposes an emotion-generation model for
complex change using a chaotic neural network (CNN). Using a CNN, the
proposed model will solve the problem of past studies that have
indicated that robotic emotion changes are simplistic. The model uses
the principle of an adaptation level, which is used in Russell's emotion
model to generate emotion. This paper considers the effectiveness of
this approach using simulation, and shows that the model can express a
change of "adaptation". In addition, through the chaos of CNN, the
proposed model can express different changes, even if the values of
CNN's input values remain the same.
https://hal.inria.fr/hal-01055587 Contributor : Hal IfipConnect in order to contact the contributor Submitted on : Wednesday, August 13, 2014 - 3:08:19 PM Last modification on : Saturday, January 8, 2022 - 6:32:01 PM Long-term archiving on: : Wednesday, November 26, 2014 - 11:51:40 PM
Hiroyuki Sumitomo, Masataka Tokumaru, Noriaki Muranaka. Study on an Emotion Generation Model for a
Robot Using a Chaotic Neural Network. 9th International Conference on Entertainment Computing (ICEC), Sep 2010, Seoul, South Korea. pp.502-504, ⟨10.1007/978-3-642-15399-0_73⟩. ⟨hal-01055587⟩