View the paper on the Frontiers in Neurorobotics website
Intrinsic motivation, the causal mechanism for spontaneous exploration
and curiosity, is a central concept in developmental psychology. It has
been argued to be a crucial mechanism for open-ended cognitive
development in humans, and as such has gathered a growing interest from
developmental roboticists in the recent years. The goal of this paper
is threefold. First, it provides a synthesis of the different
approaches of intrinsic motivation in psychology. Second, by
interpreting these approaches in a computational reinforcement learning
framework, we argue that they are not operational and even sometimes
inconsistent. Third, we set the ground for a systematic operational
study of intrinsic motivation by presenting a formal typology of
possible computational approaches. This typology is partly based on
existing computational models, but also presents new ways of
conceptualizing intrinsic motivation. We argue that this kind of
computational typology might be useful for opening new avenues for
research both in psychology and developmental robotics.
Keywords: intrinsic motivation, cognitive development, reward,
reinforcement learning, exploration, curiosity, computational modeling,
artificial intelligence, developmental robotics
Citation: Oudeyer P and Kaplan F (2007) What is intrinsic motivation? A typology of computational approaches. Front. Neurorobot. 1:6. doi:10.3389/neuro.12.006.2007
Received: 06 September 2007; paper pending published: 09 October 2007; accepted: 27 October 2007; published online: 02 November 2007.
Edited by: Max Lungarella, University of Zurich, Switzerland
Reviewed by: Jeffrey L. Krichmar, The Neurosciences Institute, USA
Cornelius Weber, Johann Wolfgang Goethe University, Germany |
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