Phuong D. H. Nguyen

BERT, are you paying attention? Attention regularization with human-annotated rationales

Elize Herrewijnen, Phuong D. H. Nguyen, Floris Bex, Albert Gatt

Attention regularisation aims to supervise the attention patterns in language models like BERT.Various studies have shown that using human-annotated rationales, in the form of highlights that explain why a text has a specific label, can have positive effects on model generalisability.In this …

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Understanding Effects and Physiological Correlates of Operator Workload Across Remote Assistance Scenarios for Automated Vehicles - Results from a User Study

Fabian Walocha, Andrea Valerio, Phuong D. H. Nguyen, Klas Ihme

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Intelligent problem-solving as integrated hierarchical reinforcement learning

Manfred Eppe, Christian Gumbsch, Matthias Kerzel, Phuong D. H. Nguyen et autres

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The Embodied Crossmodal Self Forms Language and Interaction: A Computational Cognitive Review

Frank Röder, Ozan Özdemir, Phuong D. H. Nguyen, Stefan Wermter et autres

Human language is inherently embodied and grounded in sensorimotor representations of the self and the world around it. This suggests that the body schema and ideomotor action-effect associations play an important role in language understanding, language generation, and verbal/physical interaction with others. …

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The Embodied Crossmodal Self Forms Language and Interaction: A Computational Cognitive Review

Frank Röder, Ozan Özdemir, Phuong D. H. Nguyen, Stefan Wermter et autres

Human language is inherently embodied and grounded in sensorimotor representations of the self and the world around it. This suggests that the body schema and ideomotor action-effect associations play an important role in language understanding, language generation, and verbal/physical interaction with others. …

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Sensorimotor Representation Learning for an “Active Self” in Robots: A Model Survey

Phuong D. H. Nguyen, Yasmin Kim Georgie, Ezgi Kayhan, Manfred Eppe et autres

Abstract Safe human-robot interactions require robots to be able to learn how to behave appropriately in spaces populated by people and thus to cope with the challenges posed by our dynamic and unstructured environment, rather than being provided a rigid set of …

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Sensorimotor Representation Learning for an “Active Self” in Robots: A Model Survey

Phuong D. H. Nguyen, Yasmin Kim Georgie, Ezgi Kayhan, Manfred Eppe et autres

Safe human-robot interactions require robots to be able to learn how to behave appropriately in spaces populated by people and thus to cope with the challenges posed by our dynamic and unstructured environment, rather than being provided a rigid set of rules …

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Hierarchical principles of embodied reinforcement learning: A review

Manfred Eppe, Christian Gumbsch, Matthias Kerzel, Phuong D. H. Nguyen et autres

Cognitive Psychology and related disciplines have identified several critical mechanisms that enable intelligent biological agents to learn to solve complex problems. There exists pressing evidence that the cognitive mechanisms that enable problem-solving skills in these species build on hierarchical mental representations. Among …

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Sensorimotor representation learning for an "active self" in robots: A\n model survey

Phuong D. H. Nguyen, Yasmin Kim Georgie, Ezgi Kayhan, Manfred Eppe et autres

Safe human-robot interactions require robots to be able to learn how to\nbehave appropriately in \\sout{humans' world} \\rev{spaces populated by people}\nand thus to cope with the challenges posed by our dynamic and unstructured\nenvironment, rather than being provided a rigid set of rules for …

Robotic self-representation improves manipulation skills and transfer learning

Phuong D. H. Nguyen, Manfred Eppe, Stefan Wermter

Cognitive science suggests that the self-representation is critical for learning and problem-solving. However, there is a lack of computational methods that relate this claim to cognitively plausible robots and reinforcement learning. In this paper, we bridge this gap by developing a model …

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Robotic self-representation improves manipulation skills and transfer\n learning

Phuong D. H. Nguyen, Manfred Eppe, Stefan Wermter

Cognitive science suggests that the self-representation is critical for\nlearning and problem-solving. However, there is a lack of computational methods\nthat relate this claim to cognitively plausible robots and reinforcement\nlearning. In this paper, we bridge this gap by developing a model that learns\nbidirectional action-effect …

Reinforcement Learning with Time-dependent Goals for Robotic Musicians

Thilo Fryen, Manfred Eppe, Phuong D. H. Nguyen, Timo Gerkmann et autres

Reinforcement learning is a promising method to accomplish robotic control tasks. The task of playing musical instruments is, however, largely unexplored because it involves the challenge of achieving sequential goals - melodies - that have a temporal dimension. In this paper, we …

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