Name
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. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-74889-2_37 | ACII |
Keywords | Field | DocType |
attachment bond,correct sensorimotor association,autonomous robot,minimum amount,emotional capability,developmental approach,human-robot interaction,neural architecture,affective state,uncertain environment,own model,human robot interaction | Social robot,Architecture,Communication,Computer science,Robot,Cognition,Affect (psychology) | Conference |
Volume | ISSN | Citations |
4738 | 0302-9743 | 3 |
PageRank | References | Authors |
0.50 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Antoine Hiolle | 1 | 80 | 6.72 |
| Lola Cañamero | 2 | 320 | 39.12 |
| Arnaud J. Blanchard | 3 | 24 | 2.51 |