Name
Abstract | ||
|---|---|---|
Classical conditioning is important in humans to learn and predict events in terms of associations between stimuli and to produce responses based on these associations. Social robots that have a classical conditioning skill like humans will have an advantage to interact with people more naturally, socially and effectively. In this paper, we present a novel classical conditioning mechanism and describe its implementation in ASMO cognitive architecture. The capability of this mechanism is demonstrated in the Smokey robot companion experiment. Results show that Smokey can associate stimuli and predict events in its surroundings. ASMO's classical conditioning mechanism can be used in social robots to adapt to the environment and to improve the robots' performances. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-11973-1_29 | Lecture Notes in Artificial Intelligence |
Keywords | Field | DocType |
Classical Conditioning,Maximum Likelihood Estimation,ASMO Cognitive Architecture | Social robot,Psychology,Maximum likelihood,Artificial intelligence,Cognitive architecture,Robot,Classical conditioning | Conference |
Volume | ISSN | Citations |
8755 | 0302-9743 | 1 |
PageRank | References | Authors |
0.38 | 4 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rony Novianto | 1 | 10 | 2.68 |
| Mary-anne Williams | 2 | 953 | 128.61 |
| Peter Gärdenfors | 3 | 1699 | 183.78 |
| Glenn Wightwick | 4 | 2 | 0.72 |