Abstract
To build autonomous robots able to live and interact with humans in a real-world dynamic and uncertain environment, the design of architectures permitting robots to develop attachment bonds to humans and use them to build their own model of the world is a promising avenue, not only to improve human-robot interaction and adaptation to the environment, but also as a way to develop further cognitive and emotional capabilities. In this paper we present a neural architecture to enable a robot to develop an attachment bond with a person or an object, and to discover the correct sensorimotor associations to maintain a desired affective state of well-being using a minimum amount of prior knowledge about the possible interactions with this object. © Springer-Verlag Berlin Heidelberg 2007.
Cite
CITATION STYLE
Hiolle, A., Cañamero, L., & Blanchard, A. J. (2007). Learning to Interact with the caretaker: A developmental approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4738 LNCS, pp. 422–433). Springer Verlag. https://doi.org/10.1007/978-3-540-74889-2_37
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
