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Language as a Cognitive Tool: Dall-E, Humans and Vygotskian RL Agents
In: https://hal.archives-ouvertes.fr/hal-03159786 ; 2021 (2021)
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2
Curiosity-driven exploration: Diversity of mechanisms and functions
In: https://hal.inria.fr/hal-03447896 ; 2021 (2021)
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3
SocialAI 0.1: Towards a Benchmark to Stimulate Research on Socio-Cognitive Abilities in Deep Reinforcement Learning Agents
In: https://hal.archives-ouvertes.fr/hal-03442937 ; 2021 (2021)
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SocialAI: Benchmarking Socio-Cognitive Abilities in Deep Reinforcement Learning Agents
In: https://hal.archives-ouvertes.fr/hal-03372670 ; 2021 (2021)
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5
Grounding Language to Autonomously-Acquired Skills via Goal Generation
In: ICLR 2021 - Ninth International Conference on Learning Representation ; https://hal.inria.fr/hal-03121146 ; ICLR 2021 - Ninth International Conference on Learning Representation, May 2021, Vienna / Virtual, Austria (2021)
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6
Language-Conditioned Goal Generation: a New Approach to Language Grounding in RL
In: https://hal.inria.fr/hal-03099887 ; 2021 (2021)
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7
Grounding Spatio-Temporal Language with Transformers
In: NeurIPS 2021 - 35th Conference on Neural Information Processing Systems ; https://hal.archives-ouvertes.fr/hal-03439096 ; NeurIPS 2021 - 35th Conference on Neural Information Processing Systems, Dec 2021, Virtuel, France (2021)
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8
Grounding Spatio-Temporal Language with Transformers ...
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9
Language as a Cognitive Tool to Imagine Goals in Curiosity-Driven Exploration
In: NeurIPS 2020 - 34th Conference on Neural Information Processing Systems ; https://hal.archives-ouvertes.fr/hal-03083158 ; NeurIPS 2020 - 34th Conference on Neural Information Processing Systems, Dec 2020, Vancouver / Virtual, Canada (2020)
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10
Language-Conditioned Goal Generation: a New Approach to Language Grounding for RL ...
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11
Grounding Language to Autonomously-Acquired Skills via Goal Generation ...
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12
Emergent Jaw Predominance in Vocal Development through Stochastic Optimization ...
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13
Computational and robotic models of early language development : a review
In: International handbook of language acquisition (London, 2019), p. 76-101
MPI für Psycholinguistik
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14
Computational and Robotic Models of Early Language Development: A Review
In: International Handbook of Language Acquisition ; https://hal.inria.fr/hal-02371233 ; International Handbook of Language Acquisition, 2019 (2019)
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15
Complexity Reduction in the Negotiation of New Lexical Conventions
In: 40th Annual Conference of the Cognitive Science Society (CogSci 2018) ; https://hal.inria.fr/hal-01891762 ; 40th Annual Conference of the Cognitive Science Society (CogSci 2018), Jul 2018, Madison, WI, United States (2018)
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16
Complexity Reduction in the Negotiation of New Lexical Conventions ...
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17
Complexity Reduction in the Negotiation of New Lexical Conventions ...
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18
Emergent Jaw Predominance in Vocal Development through Stochastic Optimization
In: ISSN: 2379-8920 ; EISSN: 2379-8939 ; IEEE Transactions on Cognitive and Developmental Systems ; https://hal.inria.fr/hal-01578075 ; IEEE Transactions on Cognitive and Developmental Systems, Institute of Electrical and Electronics Engineers, Inc, 2017, pp.1-12. ⟨10.1109/TCDS.2017.2704912⟩ ; http://ieeexplore.ieee.org/document/7955101/ (2017)
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19
How Evolution May Work Through Curiosity-Driven Developmental Process
In: ISSN: 1756-8757 ; EISSN: 1756-8765 ; Topics in cognitive science ; https://hal.inria.fr/hal-01404334 ; Topics in cognitive science, Wiley, 2016, 8, ⟨10.1111/tops.12196⟩ ; https://www.ncbi.nlm.nih.gov/pubmed/26969919 (2016)
Abstract: International audience ; 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 mecha- nisms yield self-organized epigenesis with emergent ordered behavioral and cognitive develop- mental 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 interac- tion 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 trajec- tory. 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.
Keyword: [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]; [INFO]Computer Science [cs]; [SCCO]Cognitive science; Curiosity; Development; Evolution; Infant active learning; Motor development; Origins of language; Robotic modelling; Self- organization; Speech development
URL: https://hal.inria.fr/hal-01404334/document
https://doi.org/10.1111/tops.12196
https://hal.inria.fr/hal-01404334/file/OudeyerSmithTopicsCogSci14.pdf
https://hal.inria.fr/hal-01404334
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20
An Alternative to Mapping a Word onto a Concept in Language Acquisition: Pragmatic Frames
In: ISSN: 1664-1078 ; Frontiers in Psychology ; https://hal.inria.fr/hal-01404385 ; Frontiers in Psychology, Frontiers, 2016, 7, pp.18. ⟨10.3389/fpsyg.2016.00470⟩ ; http://journal.frontiersin.org/article/10.3389/fpsyg.2016.00470/full (2016)
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