Maximizing learning progress: an internal reward system for development (2004)
by
Frédéric Kaplan
,
Pierre-yves Oudeyer
| Venue: | Embodied Artificial Intelligence |
| Citations: | 20 - 7 self |
BibTeX
@INPROCEEDINGS{Kaplan04maximizinglearning,
author = {Frédéric Kaplan and Pierre-yves Oudeyer},
title = {Maximizing learning progress: an internal reward system for development},
booktitle = {Embodied Artificial Intelligence},
year = {2004},
pages = {259--270},
publisher = {Springer-Verlag}
}
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Abstract
Abstract. This chapter presents a generic internal reward system that drives an agent to increase the complexity of its behavior. This reward system does not reinforce a predefined task. Its purpose is to drive the agent to progress in learning given its embodiment and the environment in which it is placed. The dynamics created by such a system are studied first in a simple environment and then in the context of active vision. 1
