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1
Formalizing Problem Solving in Computational Thinking : an Ontology approach
In: IEEE ICDL 2021 – International Conference on Development and Learning 2021 ; https://hal.inria.fr/hal-03324136 ; IEEE ICDL 2021 – International Conference on Development and Learning 2021, Aug 2021, Beijing, China (2021)
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2
Neuro-computational models of language processing
In: EISSN: 2333-9691 ; Annual Review of Linguistics ; https://hal.archives-ouvertes.fr/hal-03334485 ; Annual Review of Linguistics, Annual Reviews, In press, ⟨10.1146/lingbuzz/006147⟩ (2021)
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3
Language skill development in children with cochlear implants and the impact of age at switch-on ...
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Language skill development in children with cochlear implants and the impact of age at switch-on ...
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5
Functional Neural Architectures ...
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Functional Neural Architectures ...
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Functional Neural Architectures ...
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Burden and correlates of cognitive impairment among hypertensive patients in Tanzania: a cross-sectional study ...
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Burden and correlates of cognitive impairment among hypertensive patients in Tanzania: a cross-sectional study ...
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10
Neural correlates of language processing ...
Misra, Pranav. - : Open Science Framework, 2021
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11
A deep learning account of how language affects thought ...
Luo, Xiaoliang; Sexton, Nicholas J.; Love, Bradley C.. - : Taylor & Francis, 2021
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12
A deep learning account of how language affects thought ...
Luo, Xiaoliang; Sexton, Nicholas J.; Love, Bradley C.. - : Taylor & Francis, 2021
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13
Reflected Boundary Drift Diffusion Model: A Double Responding Framework for Go/No-Go Paradigm ...
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14
Are people still smarter than machines? If so, why? ...
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15
Can Children use Numerical Reasoning to Compare Odds in Games? ...
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Investigating the Utility of Prompting Novice Programmers for Self-Explanations to Improve Mental Models ...
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Reflected Boundary Drift Diffusion Model: A Double Responding Framework for Go/No-Go Paradigm ...
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18
Can Children use Numerical Reasoning to Compare Odds in Games? ...
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19
Does Amy Know Ben Knows You Know Your Cards? A Computational Model of Higher-Order Epistemic Reasoning ...
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20
Learning Approximate and Exact Numeral Systems via Reinforcement Learning ...
Abstract: Recent work (Xu et al., 2020) has suggested that numeral systems in different languages are shaped by a functional need for efficient communication in an information-theoretic sense. Here we take a learning-theoretic approach and show how efficient communication emerges via reinforcement learning. In our framework, two artificial agents play a Lewis signaling game where the goal is to convey a numeral concept. The agents gradually learn to communicate using reinforcement learning and the resulting numeral systems are shown to be efficient in the information-theoretic framework of Regier et al.(2015); Gibson et al. (2017). They are also shown to be similar to human numeral systems of same type. Our results thus provide a mechanistic explanation via reinforcement learning of the recent results in Xu et al. (2020) and can potentially be generalized to other semantic domains. ...
Keyword: Cognitive Linguistics; Cognitive Science; Computational Intelligence; Computational Neuroscience; Multiagent Systems; Social Psychology; Software Intelligent Agents; Translation Studies
URL: https://underline.io/lecture/27020-learning-approximate-and-exact-numeral-systems-via-reinforcement-learning
https://dx.doi.org/10.48448/4dns-y106
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