Heterogeneous Defect Prediction Based on Federated Reinforcement Learning via Gradient Clustering
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3195039
Abstract: Heterogeneous defect prediction (HDP) refers to using heterogeneous data collected by other projects to build a defect prediction model to predict the software defects in a project. Traditional methods usually involve the measurement of the… read more here.
Keywords: reinforcement learning; federated reinforcement; heterogeneous defect; model ... See more keywords
AFRL: Adaptive federated reinforcement learning for intelligent jamming defense in FANET
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Communications and Networks"
DOI: 10.1109/jcn.2020.000015
Abstract: The flying ad-hoc network (FANET) is a decentralized communication network for the unmanned aerial vehicles (UAVs). Because of the wireless nature and the unique network properties, FANET remains vulnerable to jamming attack with additional challenges.… read more here.
Keywords: reinforcement learning; federated reinforcement; fanet; adaptive federated ... See more keywords
Federated Reinforcement Learning for Energy Management of Multiple Smart Homes With Distributed Energy Resources
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2020.3035451
Abstract: This article proposesa novel federated reinforcement learning (FRL) approach for the energy management of multiple smart homes with home appliances, a solar photovoltaic system, and an energy storage system. The novelty of the proposed FRL… read more here.
Keywords: reinforcement learning; federated reinforcement; energy; energy management ... See more keywords
A Selective Federated Reinforcement Learning Strategy for Autonomous Driving
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2022.3219644
Abstract: Currently, the complex traffic environment challenges the fast and accurate response of a connected autonomous vehicle (CAV). More importantly, it is difficult for different CAVs to collaborate and share knowledge. To remedy that, this paper… read more here.
Keywords: reinforcement learning; reinforcement; federated reinforcement; knowledge ... See more keywords
Federated Reinforcement Learning in IoT: Applications, Opportunities and Open Challenges
Sign Up to like & getrecommendations! Published in 2023 at "Applied Sciences"
DOI: 10.3390/app13116497
Abstract: The internet of things (IoT) represents a disruptive concept that has been changing society in several ways. There have been several successful applications of IoT in the industry. For example, in transportation systems, the novel… read more here.
Keywords: iot applications; reinforcement learning; research; federated reinforcement ... See more keywords