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pro vyhledávání: '"Drougard, Nicolas"'
Autor:
Angelotti, Giorgio, Chanel, Caroline P. C., Pinto, Adam H. M., Lounis, Christophe, Chauffaut, Corentin, Drougard, Nicolas
The integration of physiological computing into mixed-initiative human-robot interaction systems offers valuable advantages in autonomous task allocation by incorporating real-time features as human state observations into the decision-making system.
Externí odkaz:
http://arxiv.org/abs/2402.05703
Offline estimation of the dynamical model of a Markov Decision Process (MDP) is a non-trivial task that greatly depends on the data available in the learning phase. Sometimes the dynamics of the model is invariant with respect to some transformations
Externí odkaz:
http://arxiv.org/abs/2112.09943
Learning a Markov Decision Process (MDP) from a fixed batch of trajectories is a non-trivial task whose outcome's quality depends on both the amount and the diversity of the sampled regions of the state-action space. Yet, many MDPs are endowed with i
Externí odkaz:
http://arxiv.org/abs/2111.10297
In Offline Model Learning for Planning and in Offline Reinforcement Learning, the limited data set hinders the estimate of the Value function of the relative Markov Decision Process (MDP). Consequently, the performance of the obtained policy in the r
Externí odkaz:
http://arxiv.org/abs/2105.13431
The training of autonomous agents often requires expensive and unsafe trial-and-error interactions with the environment. Nowadays several data sets containing recorded experiences of intelligent agents performing various tasks, spanning from the cont
Externí odkaz:
http://arxiv.org/abs/2010.01931
Random Forests (RFs) are strong machine learning tools for classification and regression. However, they remain supervised algorithms, and no extension of RFs to the one-class setting has been proposed, except for techniques based on second-class samp
Externí odkaz:
http://arxiv.org/abs/1611.01971
Akademický článek
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Possibilistic and qualitative POMDPs (pi-POMDPs) are counterparts of POMDPs used to model situations where the agent's initial belief or observation probabilities are imprecise due to lack of past experiences or insufficient data collection. However,
Externí odkaz:
http://arxiv.org/abs/1309.6826
Autor:
Roy, Raphaëlle N., Hinss, Marcel F., Darmet, Ludovic, Ladouce, Simon, Jahanpour, Emilie S., Somon, Bertille, Xu, Xiaoqi, Drougard, Nicolas, Dehais, Frédéric, Lotte, Fabien
Publikováno v:
Frontiers in Neuroergonomics
Frontiers in Neuroergonomics, 2022, 3, ⟨10.3389/fnrgo.2022.838342⟩
Frontiers in Neuroergonomics, 2022, 3, ⟨10.3389/fnrgo.2022.838342⟩
As is the case in several research domains, data sharing is still scarce in the field of Brain-Computer Interfaces (BCI), and particularly in that of passive BCIs—i.e., systems that enable implicit interaction or task adaptation based on a user's m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fcf6db4d795160bf6df1495677ef6f12
https://inria.hal.science/hal-03875469
https://inria.hal.science/hal-03875469
Akademický článek
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