Results 11 to 20 of about 6,522,305 (296)
Avalanche RL: A Continual Reinforcement Learning Library
, 2022 Presented at the 21st International Conference on Image Analysis and Processing (ICIAP 2021)
Lucchesi N. +3 more
openaire +3 more sources
Reinforcement Learning-based Spectrum Sharing for Cognitive Radio [PDF]
, 2011 This thesis investigates how distributed reinforcement learning-based resource assignment algorithms can be used to improve the performance of a cognitive radio system.
Jiang, Tao
core +6 more sources
RL-CycleGAN: Reinforcement Learning Aware Simulation-to-Real [PDF]
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2020)
Kanishka Rao +5 more
openaire +3 more sources
International Journal of Cognitive Computing in Engineering, 2021 Bi-objective school bus scheduling optimization problem that is a subset of vehicle fleet scheduling problem is focused in this paper. In the literature, school bus routing and scheduling problem is proven to be an NP-Hard problem.
Eda Koksal +3 more
doaj +1 more source
RL-GRIT: Reinforcement Learning for Grammar Inference [PDF]
2021 IEEE Security and Privacy Workshops (SPW), 2021 When working to understand usage of a data format, examples of the data format are often more representative than the format's specification. For example, two different applications might use very different JSON representations, or two PDF-writing applications might make use of very different areas of the PDF specification to realize the same rendered ...
openaire +3 more sources
Bayesian and variational inference for reinforcement learning [PDF]
, 2022 This thesis explores Bayesian and variational inference in the context of solving the reinforcement learning (RL) problem. Recent advances in developing state-ofthe-art algorithms suitable for continuous control introduce regularisation into the ...
Fellows, Matthew
core +1 more source
Robust Reinforcement Learning: A Review of Foundations and Recent Advances
Machine Learning and Knowledge Extraction, 2022 Reinforcement learning (RL) has become a highly successful framework for learning in Markov decision processes (MDP). Due to the adoption of RL in realistic and complex environments, solution robustness becomes an increasingly important aspect of RL ...
Janosch Moos +5 more
doaj +1 more source
CFR-RL: Traffic Engineering With Reinforcement Learning in SDN [PDF]
IEEE Journal on Selected Areas in Communications, 2020 Traditional Traffic Engineering (TE) solutions can achieve the optimal or near-optimal performance by rerouting as many flows as possible. However, they do not usually consider the negative impact, such as packet out of order, when frequently rerouting flows in the network.
Junjie Zhang 0001 +4 more
openaire +4 more sources
RL-IoT: Reinforcement Learning to Interact with IoT Devices [PDF]
2021 IEEE International Conference on Omni-Layer Intelligent Systems (COINS), 2021 Our life is getting filled by Internet of Things (IoT) devices. These devices often rely on closed or poorly documented protocols, with unknown formats and semantics. Learning how to interact with such devices in an autonomous manner is the key for interoperability and automatic verification of their capabilities.
Giulia Milan +3 more
openaire +3 more sources
Mendel, 2021 Reinforcement Learning (RL) and Deep Reinforcement Learning (DRL) methods are a promising approach to solving complex tasks in the real world with physical robots.
Roman Parak, Radomil Matousek
doaj +1 more source