Results 41 to 50 of about 34,803,504 (287)
Online Constrained Model-based Reinforcement Learning
CoRR, 2020 Conf.
Benjamin van Niekerk +2 more
openaire +4 more sources
Research on automatic pilot repetition generation method based on deep reinforcement learning
Frontiers in Neurorobotics, 2023 Using computers to replace pilot seats in air traffic control (ATC) simulators is an effective way to improve controller training efficiency and reduce training costs.
Weijun Pan +4 more
doaj +1 more source
Physics-Informed Model-Based Reinforcement Learning
CoRR, 2022 We apply reinforcement learning (RL) to robotics tasks. One of the drawbacks of traditional RL algorithms has been their poor sample efficiency. One approach to improve the sample efficiency is model-based RL. In our model-based RL algorithm, we learn a model of the environment, essentially its transition dynamics and reward function, use it to ...
Adithya Ramesh, Balaraman Ravindran
openaire +3 more sources
Gut microbiome and aging—A dynamic interplay of microbes, metabolites, and the immune system
FEBS Letters, EarlyView.Age‐dependent shifts in microbial communities engender shifts in microbial metabolite profiles. These in turn drive shifts in barrier surface permeability of the gut and brain and induce immune activation. When paired with preexisting age‐related chronic inflammation this increases the risk of neuroinflammation and neurodegenerative diseases.
Aaron Mehl, Eran Blacher
wiley +1 more source
Reconstructing enzyme evolution by protein engineering
FEBS Letters, EarlyView.Natural enzyme evolution can be retraced by protein engineering methods such as directed evolution, rational design, and ancestral sequence reconstruction. These approaches reveal how enzymes emerged from ligand‐binding scaffolds, developed varying substrate preferences, formed oligomeric complexes, adapted to environmental changes, and evolved novel ...
Lukas Drexler +2 more
wiley +1 more source
On Effective Scheduling of Model-based Reinforcement Learning
CoRR, 2021 Accepted at ...
Hang Lai +7 more
openaire +4 more sources
Molecular Oncology, EarlyView.Single‐cell multi‐omics reveals epigenetic heterogeneity across therapy‐adaptive tumor states, including quiescent/dormant, drug‐tolerant persister, and EMT‐like phenotypes. By linking regulatory features with state‐associated biomarkers, these approaches inform biomarker‐guided therapeutic strategies for evolving tumors.
Hee Jung Kim +3 more
wiley +1 more source
Ain Shams Engineering Journal, 2018 Presently, Learning Style Detection (LSD) has acquired a greater interest in the adaptive learning environment of any academic system. The existing methods of learning environment have facility such as content management and learner data analysis.
V. Balasubramanian, S. Margret Anouncia
doaj +1 more source
Molecular Oncology, EarlyView.Single‐cell DNA methylation (scDNAme) profiling maps epimutational clonal evolution, revealing mechanisms of malignancy and therapeutic resistance across diverse cancer types. By providing a high‐resolution landscape of intratumoral heterogeneity, these technologies empower precise patient stratification, guide the development of enhanced ...
Ik Soo Kim
wiley +1 more source
Aero-Engine Modeling and Control Method with Model-Based Deep Reinforcement Learning
Aerospace, 2023 Due to the strong representation ability and capability of learning from data measurements, deep reinforcement learning has emerged as a powerful control method, especially for nonlinear systems, such as the aero-engine control system.
Wenbo Gao +4 more
doaj +1 more source