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
Contributeur : Hal Ifip
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Soumis le : mercredi 13 août 2014 - 15:08:19
Dernière modification le : mercredi 16 août 2017 - 17:32:44
Document(s) archivé(s) le : mercredi 26 novembre 2014 - 23:51:40
Hiroyuki Sumitomo, Masataka Tokumaru, Noriaki Muranaka. Study on an Emotion Generation Model for a
Robot Using a Chaotic Neural Network. Hyun Seung Yang; Rainer Malaka; Junichi Hoshino; Jung Hyun Han. 9th International Conference on Entertainment Computing (ICEC), Sep 2010, Seoul, South Korea. Springer, Lecture Notes in Computer Science, LNCS-6243, pp.502-504, 2010, Entertainment Computing - ICEC 2010. 〈10.1007/978-3-642-15399-0_73〉. 〈hal-01055587〉
