Maximizing Learning Progress: An Internal Reward System for Development

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Frédéric Kaplan, Pierre-Yves Oudeyer

Published: 2003, Last Modified: 20 May 2025Embodied Artificial Intelligence 2003EveryoneRevisionsBibTeXCC BY-SA 4.0
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.