Autonomous pet-type robot with emotion behaviour-learning system based on neuromodulators

Abstract

In recent years, research on embedding human emotions in autonomous mobile robots has been carried out. Research based not only on psychological but also on physiological knowledge of emotions has also been performed, and research in neuroscience is gradually making clear the role of neuromodulators. Meanwhile, other researchers have examined the influence between neuromodulators and meta-parameters of the reinforcement system for learning. In this research, attempts are made to develop an emotion generation system for a pet-type robot based on the relationship between the human learning system's meta-parameters, emotions, and neuromodulators, such as adrenaline, noradrenaline, serotonin, and dopamine.

The proposed architecture for the emotion generation system uses a Q-learning method with meta-parameters controlled by neuromodulators. Experimental results confirming the efficiency of the method are reported.

Keywords

autonomous mobile robot emotion neuromodulators

Get full access to this article

View all access options for this article.

References

Maeda

Fuzzy rule express for emotional behaviors in an autonomous mobile robot. In Proceedings of the Seventh IFSA World Congress, vol. IV, 1997, pp. 445–450 (ACADEMIA, Prague).

Maeda

Fuzzy rule expression for emotional generation model based on subsumption architecture. In Proceedings of the 18th International Conference of the North American Fuzzy Information Processing Society, 1999, pp. 781–785 (IEEE, New York).

Nakata

Mori

Sato

Analysis of impression of robot bodily expression

J. Robotics Mechatronics, 2002, 14 (1), 27–36.

Ogata

Sugano

Emotional communication between humans and the autonomous robot WAMOEBA-2 (WasedaAmoeba) which has the emotion model

Jap. Soc. Mech. Engrs, Int. J. Ser. C, 2000, 43 (3), 568–574.

Akiguchi

Maeda

Emotion behavior learning for autonomous mobile robot based on neuromodulators In Human and artificial intelligence systems, 2004, pp. 309–314 (Advanced Knowledge International, Fukui).

Miwa

Okuchi

A new mental model for humanoid robots for human-friendly communication - introduction of learning system, mood vector and second-order equations of emotion

In Proceedings of the 2003 IEEE International Conference on Robotics and automation, 2003, pp. 3588–3593 (IEEE, New York).

Nakata

Sato

Mori

Expression of emotion and intention by robot body movement In Intelligent autonomous systems 5, 1998, pp. 352–359 (IOS Press, Amsterdam).

Maeda

Emotional generation model for autonomous mobile robot

Kansei Engng Int., 1999, 1 (1), 59–66.

Rolls

E. T.

A theory of emotion, and its application to understanding the neural basis of emotion In Neural and chemical control, 1986, pp. 325–344 (Japan Scientific Societies Press, Tokyo).

10.

Doya

Metalearning, neuromodulation and emotion

In Proceedings of the 13th Toyota Conference on Affective minds, 1999, pp. 46–47 (Elsevier Science, Mikkabi).

11.

Maslow

A. H.

Motivation and personality, 1970 (Harper & Row, New York).

12.

Wright

W. F.

Bower

G. H.

Mood effects on subjective probability assessment

Organizational Behavior Human Decision Processes, 1992, 52, 276–291.