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See detailThe leaky funnel model, a metaphor of the ventilation of the World Ocean as simulated in an OGCM
Mouchet, Anne ULg; Deleersnijder, Eric

in Tellus : Series A (2008), 60(4), 761-774

It is seen that an idealized model may suggest an appropriate scaling of the water age in the World Ocean, which is a measure of the ventilation rate. We use a 1-D advection-diffusion model in which the ... [more ▼]

It is seen that an idealized model may suggest an appropriate scaling of the water age in the World Ocean, which is a measure of the ventilation rate. We use a 1-D advection-diffusion model in which the deep ocean is represented as a leaky funnel, allowing recirculation towards the surface. The analytical solutions to the steady-state problem are readily obtained. The three parameters of the leaky funnel model are estimated in such a way that the behaviour of the domain-averaged water age be as similar as possible to that derived from a 3-D model in a series of sensitivity runs. The agreement between both sets of mean ages is excellent, with a linear correlation coefficient very close to unity. A good agreement is also found for the age of radioactive tracers and the associated radioages. The parameters of the leaky funnel model have a clear physical meaning, that is, the order of magnitude of the horizontal velocity, the mean length of water parcel trajectories in the deep ocean, and a horizontal diffusivity scale. The values of all of them turn out to be consistent with our current knowledge of the World Ocean circulation. [less ▲]

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See detailLearn-Nett : un dispositif d'apprentissage collaboratif à distance au service de la formation des enseignants. Communication présentée au séminaire de recherche 'Technologies de l'Information et de la Communication pour l'Education : instruments, dispositifs et usages, Paris, INRP
Denis, Brigitte ULg; Peeters, Robert ULg

Scientific conference (2002, March)

Présentation du dispositif d'apprentissage collaboratif Learn-Nett. Options épistémologiques, organisation, compétences visées chez les apprenants, méthodologie, tutorat.

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See detailLearn-Nett : une expérience d'apprentissage collaboratif à distance
Denis, Brigitte ULg; Peeters, Robert

in Actes du 1er congrès des chercheurs francophones en éducation (2000, May)

Présentation du dispositif d'apprentissage collaboratif (Learn-Nett).

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See detailLEARN-NETT : une expérience d'apprentissage collaboratif à distance
Charlier, Bernadette; Daele, Amaury; Docq, Françoise et al

in Le point sur la recherche en éducation en Communauté française : actes du 1er congrès des chercheurs en éducation, Bruxelles, 24-25 mai 2000 (1998)

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See detailLearned material content and acquisition level modulate cerebral reactivation during posttraining rapid-eye-movements sleep
Peigneux, Philippe ULg; Laureys, Steven ULg; Fuchs, Sonia et al

in NeuroImage (2003), 20(1), 125-134

We have previously shown that several brain areas are activated both during sequence learning at wake and during subsequent rapid-eye-movements (REM) sleep (Nat. Neurosci. 3 (2000) 831-836), suggesting ... [more ▼]

We have previously shown that several brain areas are activated both during sequence learning at wake and during subsequent rapid-eye-movements (REM) sleep (Nat. Neurosci. 3 (2000) 831-836), suggesting that REM sleep participates in the reprocessing of recent memory traces in humans. However, the nature of the reprocessed information remains open. Here, we show that regional cerebral reactivation during posttraining REM sleep is not merely related to the acquisition of basic visuomotor skills during prior practice of the serial reaction time task, but rather to the implicit acquisition of the probabilistic rules that defined stimulus sequences. Moreover, functional connections between the reactivated cuneus and the striatum-the latter being critical for implicit sequence learning-are reinforced during REM sleep after practice on a probabilistic rather than on a random sequence of stimuli. Our results therefore support the hypothesis that REM sleep is deeply involved in the reprocessing and optimization of the high-order information contained in the material to be learned. In addition, we show that the level of acquisition of probabilistic rules attained prior to sleep is correlated to the increase in regional cerebral blood flow during subsequent REM sleep. This suggests that posttraining cerebral reactivation is modulated by the strength of the memory traces developed during the learning episode. Our data provide the first experimental evidence for a link between behavioral performance and cerebral reactivation during REM sleep. (C) 2003 Elsevier Inc. All rights reserved. [less ▲]

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See detailLearner Support in the Formasup degree: variety as a key feature and close coaching to drive innovation
Poumay, Marianne ULg

in Supporting the Learner in Distance Education and E-Learning (2004)

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See detailLearning a Dictionary of Prototypical Grasp-predicting Parts from Grasping Experience
Detry, Renaud ULg; Ek, Carl Henrik; Madry, Marianna et al

in IEEE International Conference on Robotics and Automation (2013)

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See detailLearning a motor skill: Effects of blocked versus random practice. A review
Merbah, Sarah ULg; Meulemans, Thierry ULg

in Psychologica Belgica (2011), 51

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See detailLearning a motor skill: Effects of Blocked vs. Random Practice. A review
Merbah, Sarah ULg; Meulemans, Thierry ULg

in Psychologica Belgica (2011), 51(1), 15-48

Procedural learning refers to the ability to learn new perceptual, motor or cognitive skills. While many studies have explored procedural learning abilities in patients with different types of brain ... [more ▼]

Procedural learning refers to the ability to learn new perceptual, motor or cognitive skills. While many studies have explored procedural learning abilities in patients with different types of brain damage, the cognitive mechanisms involved in the acquisition of a new skill are still not well understood. The present review focuses on the conditions that optimize skill acquisition, and more specifically on the contextual interference effect (CIE), which refers to the advantage of a ‘random’ over a ‘blocked’ practice condition in skill learning tasks. According to both the ‘elaboration’ and ‘reconstruction’ hypotheses, the CIE can be explained by the fact that the random schedule requires more cognitive activity than the blocked one. However, if the CIE has been consistently demonstrated in laboratory studies, it is not so clear in fieldbased studies. We discuss this ‘laboratory and field dilemma’, and suggest that two main factors – task complexity and individual variables – may explain the discrepancy between the two types of studies. [less ▲]

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See detailA learning algorithm for synfire chains
Sougné, Jacques ULg

in French, R. (Ed.) Connectionist models of learning : Development and Evolution (2001)

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See detailLearning and Error Reproduction in Alzheimer Disease
Wansard, Murielle ULg; Erkès, jérôme; Adam, Stéphane ULg et al

Poster (2012, July 15)

Alzheimer disease (AD) is characterized by an early impairment of explicit memory processes associated to a preservation of implicit memory processes (Fleischman & Gabrieli 1998). Due to the role of ... [more ▼]

Alzheimer disease (AD) is characterized by an early impairment of explicit memory processes associated to a preservation of implicit memory processes (Fleischman & Gabrieli 1998). Due to the role of explicit memory in the suppression of errors during learning, AD patients tend to reproduce automatically (implicitly) errors that occurred during a previous learning (Baddeley & Wilson, 1994). Consequently, errorless learning should be more efficient than a classical “trial-and-error” procedure for AD patients. Indeed, errorless learning decreases the involvement of (impaired) explicit memory by avoiding the interference caused by the production of errors (Bier et al., 2002). The present study investigates the automatic post-learning error production in mild AD patients and matched control subjects by using a word stem completion task (Adam et al., 2005) in conditions of both errorless and trial-and-error learning. Results showed a lower word stem completion performance in mild AD than control subjects, but a similar performance in the patients’ group for the two learning conditions. Moreover, in the trial-and-error procedure, the errors consisted mainly in erroneous responses already produced during the learning phase. In addition, correlation analyses indicate that the ability to suppress errors in the trial-and-error learning condition in mild AD patients is subtended by the efficiency of episodic memory processes, but not by inhibitory abilities. These results suggest that the errorless procedure improves the quality of learning of mild AD patients (production of fewer errors) but do not influence the learning rate per se. [less ▲]

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See detailLearning and motivation to transfer after an e-learning programme: Impact of trainees’ motivation to train, personal interaction and satisfaction
Peters, Stéphanie ULg; Barbier, Marie ULg; Faulx, Daniel ULg et al

in Innovations in Education & Teaching International (2012), 49(4), 375-387

While e-learning appears to be increasingly present in training and education, the systematic evaluation of its effectiveness remains understudied. In this paper, we determine the mediating role of ... [more ▼]

While e-learning appears to be increasingly present in training and education, the systematic evaluation of its effectiveness remains understudied. In this paper, we determine the mediating role of satisfaction between motivation to train and personal interaction on the one hand, and learning and motivation to transfer, on the other hand. A particularity of this study is that we distinguish between different dimensions of satisfaction - enjoyment, utility, difficulty, and take into account lack of personal interaction as a variable influencing satisfaction. Results of structural equation modelling analyses show an impact of the enjoyment dimension on learning, and of the utility and difficulty dimensions on motivation to transfer. The results also stress the importance of interaction opportunities, as these have an indirect effect on learning and motivation to transfer. [less ▲]

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See detailLearning and multimedia
Denis, Brigitte ULg

in Teaching, learning, information : towards an open socratic school (1997)

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See detailLearning and Teaching Paradigms applied in e-Learning
Denis, Brigitte ULg

Conference (2008, June)

Description of teaching and learning paradigms applied in elearning environments.The model presented sustains the instructional design of such environments.

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See detailLearning and Teaching Styles
Simons, Germain ULg

Scientific conference (2001, May 16)

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See detailLearning at school, learning at labour. Some differences, some inequalities
Andre, Géraldine ULg

Conference (2007, September)

Detailed reference viewed: 2 (0 ULg)
See detailLearning Continuous Grasp Affordances by Sensorimotor Exploration
Detry, Renaud ULg; Başeski, Emre; Popović, Mila et al

in Peters, Jan; Sigaud, Olivier (Eds.) From Motor Learning to Interaction Learning in Robots (2010)

Detailed reference viewed: 38 (9 ULg)
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See detailLearning dextrous grasps that generalise to novel objects by combining hand and contact models
Kopicki, Marek; Detry, Renaud ULg; Schmidt, Florian et al

in IEEE International Conference on Robotics and Automation (2014)

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See detailLearning exploration/exploitation strategies for single trajectory reinforcement learning
Castronovo, Michaël ULg; Maes, Francis ULg; Fonteneau, Raphaël ULg et al

in Proceedings of the 10th European Workshop on Reinforcement Learning (EWRL 2012) (2012)

We consider the problem of learning high-performance Exploration/Exploitation (E/E) strategies for finite Markov Decision Processes (MDPs) when the MDP to be controlled is supposed to be drawn from a ... [more ▼]

We consider the problem of learning high-performance Exploration/Exploitation (E/E) strategies for finite Markov Decision Processes (MDPs) when the MDP to be controlled is supposed to be drawn from a known probability distribution pM( ). The performance criterion is the sum of discounted rewards collected by the E/E strategy over an in finite length trajectory. We propose an approach for solving this problem that works by considering a rich set of candidate E/E strategies and by looking for the one that gives the best average performances on MDPs drawn according to pM( ). As candidate E/E strategies, we consider index-based strategies parametrized by small formulas combining variables that include the estimated reward function, the number of times each transition has occurred and the optimal value functions V and Q of the estimated MDP (obtained through value iteration). The search for the best formula is formalized as a multi-armed bandit problem, each arm being associated with a formula. We experimentally compare the performances of the approach with R-max as well as with e-Greedy strategies and the results are promising. [less ▲]

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See detailLearning for exploration/exploitation in reinforcement learning
Castronovo, Michaël ULg

Master's dissertation (2012)

We consider the problem of learning high-performance Exploration/Exploitation (E/E) strategies for finite Markov Decision Processes (MDPs) when the MDP to be controlled is supposed to be drawn from a ... [more ▼]

We consider the problem of learning high-performance Exploration/Exploitation (E/E) strategies for finite Markov Decision Processes (MDPs) when the MDP to be controlled is supposed to be drawn from a known probability distribution pM(·). The performance criterion is the sum of discounted rewards collected by the E/E strategy over an infinite length trajectory. We propose an approach for solving this problem that works by considering a rich set of candidate E/E strategies and by looking for the one that gives the best average performances on MDPs drawn according to pM(·). As candidate E/E strategies, we consider index-based strategies parametrized by small formulas combining variables that include the estimated reward function, the number of times each transition has occurred and the optimal value functions ˆ V and ˆQ of the estimated MDP (obtained through value iteration). The search for the best formula is formalized as a multi-armed bandit problem, each arm being associated with a formula. We experimentally compare the performances of the approach with R-max as well as with -Greedy strategies and the results are promising. [less ▲]

Detailed reference viewed: 43 (5 ULg)