Intrinsic motivation, curiosity and learning: theory and applications in educational technologies

Pierre-Yves Oudeyer 1 Jacqueline Gottlieb 2 Manuel Lopes 1
1 Flowers - Flowing Epigenetic Robots and Systems
Inria Bordeaux - Sud-Ouest, U2IS - Unité d'Informatique et d'Ingénierie des Systèmes
Abstract : This article studies the bi-directional causal interactions between curiosity and learning, and discusses how understanding these interactions can be leveraged in educational technology applications. First, we review recent results showing how state curiosity, and more generally the experience of novelty and surprise, can enhance learning and memory retention. Then, we discuss how psychology and neuroscience have conceptualized curiosity and intrinsic motivation, studying how the brain can be intrinsically rewarded by novelty, complexity or other measures of information. We explain how the framework of computational reinforcement learning can be used to model such mechanisms of curiosity. Then, we discuss the learning progress (LP) hypothesis, which posits a positive feedback loop between curiosity and learning. We outline experiments with robots that show how LP-driven attention and exploration can self-organize a developmental learning curriculum scaffolding efficient acquisition of multiple skills/tasks.. Finally, we discuss recent work exploiting these conceptual and computational models in educational technologies, showing in particular how Intelligent Tutoring Systems can be designed to foster curiosity and learning.
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Pierre-Yves Oudeyer, Jacqueline Gottlieb, Manuel Lopes. Intrinsic motivation, curiosity and learning: theory and applications in educational technologies. Progress in brain research, Elsevier, 2016, 229, pp.257-284. 〈http://www.sciencedirect.com/science/article/pii/S0079612316300589〉. 〈10.1016/bs.pbr.2016.05.005〉. 〈hal-01404278〉

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