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Intrinsically motivated spontaneous exploration is a key enabler of autonomous developmental learning in human children.
Curiosity and exploration
Daniel E Berlyne · 1966
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Multidimensional binary search trees used for associative searching
Jon Louis Bentley · 1975
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Integrated architectures for learning, planning, and reacting based on approximating dynamic programming
Richard S Sutton · 1990
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A possibility for implementing curiosity and boredom in model-building neural controllers
Jürgen Schmidhuber · 1991
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Learning to achieve goals
Leslie Pack Kaelbling · 1993
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Exploration bonuses and dual control
Peter Dayan and Terrence J Sejnowski · 1996
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A dynamic systems approach to the development of cognition and action
Esther Thelen and Linda B Smith · 1996
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The scientist in the crib: Minds, brains, and how children learn
Alison Gopnik, Andrew N Meltzoff, and Patricia K Kuhl · 1999
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Maximizing learning progress: an internal reward system for development
Frédéric Kaplan and Pierre-Yves Oudeyer · 2004
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What is intrinsic motivation? A typology of computational approaches
Pierre-Yves. Oudeyer and F. Kaplan · 2007
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Intrinsic Motivation Systems for Autonomous Mental Development
Pierre-Yves Oudeyer, Frdric Kaplan, and Verena V. Hafner · 2007
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Curriculum learning
Yoshua Bengio, Jérôme Louradour, Ronan Collobert, and Jason Weston · 2009
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Intrinsically motivated goal exploration for active motor learning in robots: A case study
Adrien Baranes and Pierre-Yves Oudeyer · 2010
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Maturationally-constrained competence-based intrinsically motivated learning
Adrien Baranes and Pierre-Yves Oudeyer · 2010
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Goal babbling permits direct learning of inverse kinematics
Matthias Rolf, Jochen J Steil, and Michael Gienger · 2010
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When novelty is not enough
Giuseppe Cuccu and Faustino Gomez · 2011
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Intrinsically Motivated Learning in Natural and Artificial Systems
Gianluca Baldassarre and Marco Mirolli · 2013
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Active learning of inverse models with intrinsically motivated goal exploration in robots
Adrien Baranes and Pierre-Yves Oudeyer · 2013
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Intrinsic motivation and reinforcement learning
Andrew G Barto · 2013
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Information-seeking, curiosity, and attention: computational and neural mechanisms
Jacqueline Gottlieb, Pierre-Yves Oudeyer, Manuel Lopes, and Adrien Baranes · 2013
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First experiments with powerplay
Rupesh Kumar Srivastava, Bas R Steunebrink, and Jürgen Schmidhuber · 2013
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Poppy Project: Open-Source Fabrication of 3D Printed Humanoid Robot for Science, Education and Art
Matthieu Lapeyre, Pierre Rouanet, Jonathan Grizou, Steve Nguyen, Fabien Depraetre, Alexandre Le Falher, and Pierre-Yves Oudeyer · 2014
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Self-organization of early vocal development in infants and machines: the role of intrinsic motivation
Clément Moulin-Frier, Sao M. Nguyen, and Pierre-Yves Oudeyer · 2014
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Wojciech Sutskever, Ilya Zaremba · 2014
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Robots that can adapt like animals
Antoine Cully, Jeff Clune, Danesh Tarapore, and Jean-Baptiste Mouret · 2015
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Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
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The psychology and neuroscience of curiosity
Celeste Kidd and Benjamin Y Hayden · 2015
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Universal value function approximators
Tom Schaul, Daniel Horgan, Karol Gregor, and David Silver · 2015
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Why greatness cannot be planned: The myth of the objective
Kenneth O Stanley and Joel Lehman · 2015
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Unifying count-based exploration and intrinsic motivation
Marc Bellemare, Sriram Srinivasan, Georg Ostrovski, Tom Schaul, David Saxton, and Remi Munos · 2016
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GEP-PG: Decoupling exploration and exploitation in deep reinforcement learning algorithms
Cédric Colas, Olivier Sigaud, and Pierre-Yves Oudeyer · 2018
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Noisy networks for exploration
Meire Fortunato, Mohammad Gheshlaghi Azar, Bilal Piot, Jacob Menick, Matteo Hessel, Ian Osband, Alex Graves, Volodymyr Mnih, Rémi Munos, Demis Hassabis, Olivier Pietquin, Charles Blundell, and Shane Legg · 2018
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Towards a neuroscience of active sampling and curiosity
Jacqueline Gottlieb and Pierre-Yves Oudeyer · 2018
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Curiosity driven exploration of learned disentangled goal spaces
Adrien Laversanne-Finot, Alexandre Pere, and Pierre-Yves Oudeyer · 2018
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Visual reinforcement learning with imagined goals
Ashvin Nair, Vitchyr Pong, Murtaza Dalal, Shikhar Bahl, Steven Lin, and Sergey Levine · 2018
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Parameter space noise for exploration
Matthias Plappert, Rein Houthooft, Prafulla Dhariwal, Szymon Sidor, Richard Y. Chen, Xi Chen, Tamim Asfour, Pieter Abbeel, and Marcin Andrychowicz · 2018
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Modular active curiosity-driven discovery of tool use
Sébastien Forestier and Pierre-Yves Oudeyer · 2016
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Vime: Variational information maximizing exploration
Rein Houthooft, Xi Chen, Yan Duan, John Schulman, Filip De Turck, and Pieter Abbeel · 2016
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Hierarchical deep reinforcement learning: Integrating temporal abstraction and intrinsic motivation
Tejas D Kulkarni, Karthik Narasimhan, Ardavan Saeedi, and Josh Tenenbaum · 2016
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What learning systems do intelligent agents need? complementary learning systems theory updated
Dharshan Kumaran, Demis Hassabis, and James L McClelland · 2016
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How evolution may work through curiosity-driven developmental process
Pierre-Yves Oudeyer and Linda B Smith · 2016
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Intrinsic motivation, curiosity, and learning: Theory and applications in educational technologies
Pierre-Yves Oudeyer, Jacqueline Gottlieb, and Manuel Lopes · 2016
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Unsupervised learning of goal spaces for intrinsically motivated goal exploration
Alexandre Péré, Sébastien Forestier, Olivier Sigaud, and Pierre-Yves Oudeyer · 2018
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Learning by playing solving sparse reward tasks from scratch
Martin A Riedmiller, Roland Hafner, Thomas Lampe, Michael Neunert, Jonas Degrave, Tom Van de Wiele, Vlad Mnih, Nicolas Heess, and Jost Tobias Springenberg · 2018
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Control what you can: Intrinsically motivated task-planning agent
Sebastian Blaes, Marin Vlastelica Pogančić, Jiajie Zhu, and Georg Martius · 2019
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CURIOUS: Intrinsically motivated modular multi-goal reinforcement learning
Cédric Colas, Pierre-Yves Oudeyer, Olivier Sigaud, Pierre Fournier, and Mohamed Chetouani · 2019
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Teacher algorithms for curriculum learning of deep rl in continuously parameterized environments
Rémy Portelas, Cédric Colas, Katja Hofmann, and Pierre-Yves Oudeyer · 2019
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Automated curriculum generation through setter-solver interactions
Sebastien Racaniere, Andrew Lampinen, Adam Santoro, David Reichert, Vlad Firoiu, and Timothy Lillicrap · 2019
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Autonomous reinforcement learning of multiple interrelated tasks
Vieri Giuliano Santucci, Gianluca Baldassarre, and Emilio Cartoni · 2019
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Designing neural networks through neuroevolution
Kenneth O Stanley, Jeff Clune, Joel Lehman, and Risto Miikkulainen · 2019
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Curiosity and exploration
Marina Bazhydai, Katherine Twomey, and Gert Westermann · 2020
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A curious formulation robot enables the discovery of a novel protocell behavior
Jonathan Grizou, Laurie J. Points, Abhishek Sharma, and Leroy Cronin · 2020
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Maximum entropy gain exploration for long horizon multi-goal reinforcement learning
Silviu Pitis, Harris Chan, Stephen Zhao, Bradly C. Stadie, and Jimmy Ba · 2020
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Skew-fit: State-covering self-supervised reinforcement learning
Vitchyr Pong, Murtaza Dalal, Steven Lin, Ashvin Nair, Shikhar Bahl, and Sergey Levine · 2020
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Automatic curriculum learning for deep RL: A short survey
Rémy Portelas, Cédric Colas, Lilian Weng, Katja Hofmann, and Pierre-Yves Oudeyer · 2020
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Intrinsically motivated exploration for automated discovery of patterns in morphogenetic systems
Chris Reinke, Mayalen Etcheverry, and Pierre-Yves Oudeyer · 2020
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Variational Empowerment as Representation Learning for Goal-Based Reinforcement Learning, 2021
Jongwook Choi, Archit Sharma, Honglak Lee, Sergey Levine, and Shixiang Shane Gu · 2021
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First return, then explore
Adrien Ecoffet, Joost Huizinga, Joel Lehman, Kenneth O Stanley, and Jeff Clune · 2021
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Intelligent behavior depends on the ecological niche
Manfred Eppe and Pierre-Yves Oudeyer · 2021
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Autotelic agents with intrinsically motivated goal-conditioned reinforcement learning: a short survey
Cédric Colas, Tristan Karch, Olivier Sigaud, and Pierre-Yves Oudeyer · 2022
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