The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
How Evolution May Work Through Curiosity‐Driven Developmental Process
Open accessAbstract
Infants' own activities create and actively select their learning experiences. Here we review recent models of embodied information seeking and curiosity‐driven learning and show that these mechanisms have deep implications for development and evolution. We discuss how these mechanisms yield self‐organized epigenesis with emergent ordered behavioral and cognitive developmental stages. We describe a robotic experiment that explored the hypothesis that progress in learning, in and for itself, generates intrinsic rewards: The robot learners probabilistically selected experiences according to their potential for reducing uncertainty. In these experiments, curiosity‐driven learning led the robot learner to successively discover object affordances and vocal interaction with its peers. We explain how a learning curriculum adapted to the current constraints of the learning system automatically formed, constraining learning and shaping the developmental trajectory. The observed trajectories in the robot experiment share many properties with those in infant development, including a mixture of regularities and diversities in the developmental patterns. Finally, we argue that such emergent developmental structures can guide and constrain evolution, in particular with regard to the origins of language.
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Cites
The origins of intelligence in children.
Piaget, J. (1952) · doi:10.1037/11494-000 · Cited by 10,687
The psychology of curiosity: A review and reinterpretation.
Loewenstein, G. (1994) · Psychological Bulletin · doi:10.1037/0033-2909.116.1.75 · Cited by 2,738 · cited 1×
“Such intrinsically motivating activities have been called “progress niches” (Oudeyer et al., 2007): progress in learning in and for itself generates intrinsic rewards and an action selection system directly aims to maximize this reward.”
BackgroundEncyclopedia of the Sciences of Learning
(2012) · doi:10.1007/978-1-4419-1428-6 · Cited by 1,091
What is intrinsic motivation? A typology of computational approaches
Oudeyer, P.-Y. (2007) · Frontiers in Neurorobotics · doi:10.3389/neuro.12.006.2007 · Cited by 811
Information-seeking, curiosity, and attention: computational and neural mechanisms
Gottlieb, J., Oudeyer, P.-Y., Lopes, M., & Baranes, A. (2013) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2013.09.001 · Cited by 784
Self-citationPerceptions as Hypotheses: Saccades as Experiments
Friston, K., Adams, R. A., Perrinet, L., & Breakspear, M. (2012) · Frontiers in Psychology · doi:10.3389/fpsyg.2012.00151 · Cited by 462
Cited by
The Psychology and Neuroscience of Curiosity
Kidd, C., & Hayden, B. Y. (2015) · Neuron · doi:10.1016/j.neuron.2015.09.010 · Cited by 1,026
The Developing Infant Creates a Curriculum for Statistical Learning
Smith, L. B., Jayaraman, S., Clerkin, E., & Yu, C. (2018) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2018.02.004 · Cited by 299
Self-citationWhen Is More Uncertainty Better? A Model of Uncertainty Regulation and Effectiveness
Griffin, M. A., & Grote, G. (2020) · Academy of Management Review · doi:10.5465/amr.2018.0271 · Cited by 223
A nice surprise? Predictive processing and the active pursuit of novelty
Clark, A. (2018) · Phenomenology and the Cognitive Sciences · doi:10.1007/s11097-017-9525-z · Cited by 156
Play in predictive minds: A cognitive theory of play.
Andersen, M. M., Kiverstein, J., Miller, M., & Roepstorff, A. (2023) · Psychological Review · doi:10.1037/rev0000369 · Cited by 122
Metadata
- Authors
- Oudeyer, P., & Smith, L. B.
- Venue
- Topics in Cognitive Science
- Publisher
- Wiley
- Published
- 2016-03-11
- Volume
- 8
- Issue
- 2
- Pages
- 492-502
- ISSN
- 1756-8757 (ISSN-L)
- 1756-8765
- OpenAlex
- W2296598215
- Cited by
- 191
- References
- 6
- FWCI
- 13.28
- Type
- journal article
- Language
- en
- Open access
- bronze
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