Abstract
This paper discusses various techniques to let an agent learn how to predict the effects of its own actions on its sensor data autonomously, and their usefulness to apply them to visual sensors. An Extreme Learning Machine is used for visuomotor prediction, while various autonomous control techniques that can aid the prediction process by balancing exploration and exploitation are discussed and tested in a simple system: a camera moving over a 2D greyscale image.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of BNAIC 2013: 25th Belgium-Netherlands Conference on Artificial Intelligence |
| Pages | 1-8 |
| Number of pages | 8 |
| Publication status | Published - 2013 |
| Externally published | Yes |
| Event | 25th Benelux Conference on Artificial Intelligence (BNAIC2013) - Delft, Netherlands Duration: 7 Nov 2013 → 8 Nov 2013 Conference number: 25 |
Conference
| Conference | 25th Benelux Conference on Artificial Intelligence (BNAIC2013) |
|---|---|
| Abbreviated title | BNAIC 2013 |
| Country/Territory | Netherlands |
| City | Delft |
| Period | 7/11/13 → 8/11/13 |
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