Zobrazeno 1 - 10
of 727
pro vyhledávání: '"P. Sigaud"'
Autor:
Aissi, Mohamed Salim, Romac, Clement, Carta, Thomas, Lamprier, Sylvain, Oudeyer, Pierre-Yves, Sigaud, Olivier, Soulier, Laure, Thome, Nicolas
Reinforcement learning (RL) is a promising approach for aligning large language models (LLMs) knowledge with sequential decision-making tasks. However, few studies have thoroughly investigated the impact on LLM agents capabilities of fine-tuning them
Externí odkaz:
http://arxiv.org/abs/2410.19920
Autor:
Gaven, Loris, Romac, Clement, Carta, Thomas, Lamprier, Sylvain, Sigaud, Olivier, Oudeyer, Pierre-Yves
The past years have seen Large Language Models (LLMs) strive not only as generative models but also as agents solving textual sequential decision-making tasks. When facing complex environments where their zero-shot abilities are insufficient, recent
Externí odkaz:
http://arxiv.org/abs/2410.12481
Vision-language models (VLMs) have tremendous potential for grounding language, and thus enabling language-conditioned agents (LCAs) to perform diverse tasks specified with text. This has motivated the study of LCAs based on reinforcement learning (R
Externí odkaz:
http://arxiv.org/abs/2409.16024
Under the ACA, the federal government paid a substantially larger share of medical costs of newly eligible Medicaid enrollees than previously eligible ones. States could save up to 100% of their per-enrollee costs by reclassifying original enrollees
Externí odkaz:
http://arxiv.org/abs/2407.07217
Applying reinforcement learning (RL) to real-world applications requires addressing a trade-off between asymptotic performance, sample efficiency, and inference time. In this work, we demonstrate how to address this triple challenge by leveraging par
Externí odkaz:
http://arxiv.org/abs/2407.02217
Certificate-of-need (CON) laws require that healthcare providers receive approval from a state board before offering additional services in a given community. Proponents of CON laws claim that these laws are needed to prevent the oversupply of health
Externí odkaz:
http://arxiv.org/abs/2405.08168
Demonstrations are commonly used to speed up the learning process of Deep Reinforcement Learning algorithms. To cope with the difficulty of accessing multiple demonstrations, some algorithms have been developed to learn from a single demonstration. I
Externí odkaz:
http://arxiv.org/abs/2402.09355
Autor:
Sigaud, Olivier, Baldassarre, Gianluca, Colas, Cedric, Doncieux, Stephane, Duro, Richard, Oudeyer, Pierre-Yves, Perrin-Gilbert, Nicolas, Santucci, Vieri Giuliano
A lot of recent machine learning research papers have ``open-ended learning'' in their title. But very few of them attempt to define what they mean when using the term. Even worse, when looking more closely there seems to be no consensus on what dist
Externí odkaz:
http://arxiv.org/abs/2311.00344
Autor:
Raffin, Antonin, Sigaud, Olivier, Kober, Jens, Albu-Schäffer, Alin, Silvério, João, Stulp, Freek
In search of a simple baseline for Deep Reinforcement Learning in locomotion tasks, we propose a model-free open-loop strategy. By leveraging prior knowledge and the elegance of simple oscillators to generate periodic joint motions, it achieves respe
Externí odkaz:
http://arxiv.org/abs/2310.05808
Autor:
Aurélie Briane, Valérie Horvais, Marianne Sigaud, Marc Trossaërt, Nicolas Drillaud, Catherine Ternisien, Marc Fouassier, Antoine Babuty
Publikováno v:
eJHaem, Vol 5, Iss 5, Pp 964-970 (2024)
Abstract Treatment of type 3 von Willebrand disease by infusion of von Willebrand factor (VWF) and factor VIII (FVIII) concentrates may lead to the development of anti‐VWF antibodies, challenging haemostasis management. The systematic review of the
Externí odkaz:
https://doaj.org/article/d6a73bb4dec94851b6773375cd734b50
