Zobrazeno 1 - 10
of 22 859
pro vyhledávání: '"A A, Alcantara"'
Autor:
Aragão, Francisco, Alcântara, João
When we merge information in Dempster-Shafer Theory (DST), we are faced with anomalous behavior: agents with equal expertise and credibility can have their opinion disregarded after resorting to the belief combination rule of this theory. This proble
Externí odkaz:
http://arxiv.org/abs/2408.08928
Multi-agent reinforcement learning for the control of three-dimensional Rayleigh-B\'enard convection
Autor:
Vasanth, Joel, Rabault, Jean, Alcántara-Ávila, Francisco, Mortensen, Mikael, Vinuesa, Ricardo
Deep reinforcement learning (DRL) has found application in numerous use-cases pertaining to flow control. Multi-agent RL (MARL), a variant of DRL, has shown to be more effective than single-agent RL in controlling flows exhibiting locality and transl
Externí odkaz:
http://arxiv.org/abs/2407.21565
Autor:
Jeon, Joongoo, Rabault, Jean, Vasanth, Joel, Alcántara-Ávila, Francisco, Baral, Shilaj, Vinuesa, Ricardo
Flow control is key to maximize energy efficiency in a wide range of applications. However, traditional flow-control methods face significant challenges in addressing non-linear systems and high-dimensional data, limiting their application in realist
Externí odkaz:
http://arxiv.org/abs/2407.17822
Designing active-flow-control (AFC) strategies for three-dimensional (3D) bluff bodies is a challenging task with critical industrial implications. In this study we explore the potential of discovering novel control strategies for drag reduction usin
Externí odkaz:
http://arxiv.org/abs/2405.17210
This study presents novel active-flow-control (AFC) strategies aimed at achieving drag reduction for a three-dimensional cylinder immersed in a flow at a Reynolds number based on freestream velocity and cylinder diameter of (Re_D=3900). The cylinder
Externí odkaz:
http://arxiv.org/abs/2405.17655
Logistic regression is widely used in many areas of knowledge. Several works compare the performance of lasso and maximum likelihood estimation in logistic regression. However, part of these works do not perform simulation studies and the remaining o
Externí odkaz:
http://arxiv.org/abs/2404.17482
The control efficacy of classical periodic forcing and deep reinforcement learning (DRL) is assessed for a turbulent separation bubble (TSB) at $Re_\tau=180$ on the upstream region before separation occurs. The TSB can resemble a separation phenomeno
Externí odkaz:
http://arxiv.org/abs/2403.20295
Autor:
Masur, Pietro B. S., Oliveira, Francisco Braulio, Medino, Lucas Moreira, Huber, Emanuel, Padilha, Milene Haraguchi, de Alcantara, Cassio, Sellaro, Renata
Lip segmentation is crucial in computer vision, especially for lip reading. Despite extensive face segmentation research, lip segmentation has received limited attention. The aim of this study is to compare state-of-the-art lip segmentation models us
Externí odkaz:
http://arxiv.org/abs/2311.11992
Autor:
Suárez, Joseph, Isola, Phillip, Choe, Kyoung Whan, Bloomin, David, Li, Hao Xiang, Pinnaparaju, Nikhil, Kanna, Nishaanth, Scott, Daniel, Sullivan, Ryan, Shuman, Rose S., de Alcântara, Lucas, Bradley, Herbie, Castricato, Louis, You, Kirsty, Jiang, Yuhao, Li, Qimai, Chen, Jiaxin, Zhu, Xiaolong
Neural MMO 2.0 is a massively multi-agent environment for reinforcement learning research. The key feature of this new version is a flexible task system that allows users to define a broad range of objectives and reward signals. We challenge research
Externí odkaz:
http://arxiv.org/abs/2311.03736
Autor:
Günder, Maurice, Yamati, Facundo Ramón Ispizua, Alcántara, Abel Andree Barreto, Mahlein, Anne-Katrin, Sifa, Rafet, Bauckhage, Christian
Remote sensing and artificial intelligence are pivotal technologies of precision agriculture nowadays. The efficient retrieval of large-scale field imagery combined with machine learning techniques shows success in various tasks like phenotyping, wee
Externí odkaz:
http://arxiv.org/abs/2311.03076