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1
Didactique de la prononciation en langues étrangères : de la correction à une médiation
Miras, Grégory. - Paris : Didier, 2021
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UB Frankfurt Linguistik
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2
Cognitive factors in perception and imitation of Thai tones by Mandarin versus Vietnamese speakers
Chen, Juqiang. - 2020
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3
In kind : the enactive poem and the co-creative response
Errington, Patrick. - : University of St Andrews, 2019. : The University of St Andrews, 2019
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4
La prosodie : un support à la création musicale dans l'œuvre In the Key of K
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5
Is High Fidelity Imitation Necessary for Cumulative Culture? An Analysis of the Ratchet Argument
Ferrario, Chiara Elettra. - : Victoria University of Wellington, 2018
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6
Causes and Consequences of Convergence
Heath, Jevon Scot. - : eScholarship, University of California, 2017
In: Heath, Jevon Scot. (2017). Causes and Consequences of Convergence. UC Berkeley: Linguistics. Retrieved from: http://www.escholarship.org/uc/item/7ft935nw (2017)
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7
Lexical Tone Gestures ...
Yi, Hao. - : Zenodo, 2017
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8
Lexical Tone Gestures ...
Yi, Hao. - : Zenodo, 2017
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9
Adjusting linguistically to others: the role of social context In lexical choices and spatial language
Tosi, Alessia. - : The University of Edinburgh, 2017
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10
Cognitive mechanisms and social consequences of imitation
Lelonkiewicz, Jarosław Roman. - : The University of Edinburgh, 2017
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11
Motor Aspects of the Emergence of Oral Gestures for Speech: A Dynamic Approach
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12
Generic Reinforcement Learning Beyond Small MDPs
Daswani, Mayank. - 2016
Abstract: Feature reinforcement learning (FRL) is a framework within which an agent can automatically reduce a complex environment to a Markov Decision Process (MDP) by finding a map which aggregates similar histories into the states of an MDP. The primary motivation behind this thesis is to build FRL agents that work in practice, both for larger environments and larger classes of environments. We focus on empirical work targeted at practitioners in the field of general reinforcement learning, with theoretical results wherever necessary. The current state-of-the-art in FRL uses suffix trees which have issues with large observation spaces and long-term dependencies. We start by addressing the issue of long-term dependency using a class of maps known as looping suffix trees, which have previously been used to represent deterministic POMDPs. We show the best existing results on the TMaze domain and good results on larger domains that require long-term memory. We introduce a new value-based cost function that can be evaluated model-free. The value- based cost allows for smaller representations, and its model-free nature allows for its extension to the function approximation setting, which has computational and representational advantages for large state spaces. We evaluate the performance of this new cost in both the tabular and function approximation settings on a variety of domains, and show performance better than the state-of-the-art algorithm MC-AIXI-CTW on the domain POCMAN. When the environment is very large, an FRL agent needs to explore systematically in order to find a good representation. However, it needs a good representation in order to perform this systematic exploration. We decouple both by considering a different setting, one where the agent has access to the value of any state-action pair from an oracle in a training phase. The agent must learn an approximate representation of the optimal value function. We formulate a regression-based solution based on online learning methods to build an such an agent. We test this agent on the Arcade Learning Environment using a simple class of linear function approximators. While we made progress on the issue of scalability, two major issues with the FRL framework remain: the need for a stochastic search method to minimise the objective function and the need to store an uncompressed history, both of which can be very computationally demanding.
Keyword: AGI; Arcade Learning Environment; artificial intelligence; Atari games; DAgger; function approximation; general learning agents; imitation learning; looping suffix trees; Markov Decision Processes; MDP; partially observable; POMDP; reinforcement learning; suffix trees
URL: http://hdl.handle.net/1885/110545
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13
Yiddish Imitations in German Literature. Studies towards Fictional Language Structure ... : Imitationen des Jiddischen in der deutschsprachigen Literatur. Studien zur Struktur fiktionaler Sprache ...
Schäfer, Lea. - : Philipps-Universität Marburg, 2016
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14
Simulating imitative learning in a humanoid robot for the purpose of language acquisition
Sheih, Annlin. - 2016
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15
“You Say What I Say”: The Value of Studying Elicited Verbal Imitation in Toddlers
Hodges, Rosemary Amanda. - : The University of Sydney, 2016. : Discipline of Speech Pathology, 2016. : Faculty of Health Sciences, 2016
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16
Imitation of words and actions across cultures
Klinger, Jörn. - 2015
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17
Imitationen des Jiddischen in der deutschsprachigen Literatur. Studien zur Struktur fiktionaler Sprache
Lea; Aptroot; Schäfer. - : Philipps-Universität Marburg, 2014. : Germanistische Sprachwissenschaft, 2014
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18
Exploring the Relationship between Imitation and Social Communication in Infants
Hanika, Leslie. - 2014
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19
Akustik des Vokals : Präliminarien
Maurer, Dieter. - Zürich [u.a.] : IPF [u.a.], 2013
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UB Frankfurt Linguistik
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20
Speech imitation: the cognitive underpinnings of adaptive vocal behaviour
Nguyen, Noël; Sato, Marc; Postma-Nilsenová, Marie. - : HAL CCSD, 2013. : Frontiers in Psychology, 2013
In: https://hal.archives-ouvertes.fr/hal-00986119 ; France. Frontiers in Psychology, 2013 (2013)
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