Multiagent reinforcement learning for strictly constrained tasks based on Reward Recorder
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.22945
Abstract: Multiagent reinforcement learning (MARL) has been widely applied in engineering problems. However, many strictly constrained problems such as distributed optimization in engineering applications are still a great challenge to MARL. Especially for strict global constraints… read more here.
Keywords: reinforcement learning; reinforcement; strictly constrained; reward recorder ... See more keywords
Hierarchical multiagent reinforcement learning schemes for air traffic management
Sign Up to like & getrecommendations! Published in 2021 at "Neural Computing and Applications"
DOI: 10.1007/s00521-021-05748-7
Abstract: In this work we investigate the use of hierarchical multiagent reinforcement learning methods for the computation of policies to resolve congestion problems in the air traffic management domain. To address cases where the demand of… read more here.
Keywords: reinforcement learning; reinforcement; air traffic; multiagent reinforcement ... See more keywords
Multiagent Reinforcement Learning-Based Adaptive Sampling for Conformational Dynamics of Proteins.
Sign Up to like & getrecommendations! Published in 2022 at "Journal of chemical theory and computation"
DOI: 10.1021/acs.jctc.2c00683
Abstract: Machine learning is increasingly applied to improve the efficiency and accuracy of molecular dynamics (MD) simulations. Although the growth of distributed computer clusters has allowed researchers to obtain higher amounts of data, unbiased MD simulations… read more here.
Keywords: adaptive sampling; reinforcement learning; based adaptive; learning based ... See more keywords
FMRQ—A Multiagent Reinforcement Learning Algorithm for Fully Cooperative Tasks
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Cybernetics"
DOI: 10.1109/tcyb.2016.2544866
Abstract: In this paper, we propose a multiagent reinforcement learning algorithm dealing with fully cooperative tasks. The algorithm is called frequency of the maximum reward Q-learning (FMRQ). FMRQ aims to achieve one of the optimal Nash… read more here.
Keywords: cooperative tasks; reinforcement learning; fully cooperative; learning algorithm ... See more keywords
Multiagent Reinforcement Learning for Energy Management in Residential Buildings
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2020.2977104
Abstract: The aim of this article is to explore the multiagent reinforcement learning approach for residential multicarrier energy management. Defining the multiagents system not only enhances the possibility of dedicating separate demand response programs for different… read more here.
Keywords: energy management; multiagent reinforcement; energy; reinforcement learning ... See more keywords
Hybrid Multiagent Reinforcement Learning for Electric Vehicle Resilience Control Towards a Low-Carbon Transition
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2022.3166215
Abstract: In responseto low-carbon requirements, a large amount of renewable energy resources (RESs) have been deployed in power systems; nevertheless, the intermittency of RESs raises the system vulnerability and even causes severe damage under extreme events.… read more here.
Keywords: resilience; carbon; reinforcement learning; control ... See more keywords
Neighborhood Cooperative Multiagent Reinforcement Learning for Adaptive Traffic Signal Control in Epidemic Regions
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2022.3173490
Abstract: Nowadays, multiagent reinforcement learning (MARL) have shared significant advances in the adaptive traffic signal control (ATSC) problems. For most of the researches, agents are all isomorphic, which disregards the situation in which isomerous intersections cooperative… read more here.
Keywords: traffic signal; reinforcement learning; adaptive traffic; hdqn ... See more keywords
Learning Automata-Based Multiagent Reinforcement Learning for Optimization of Cooperative Tasks
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2020.3025711
Abstract: Multiagent reinforcement learning (MARL) has been extensively used in many applications for its tractable implementation and task distribution. Learning automata, which can be classified under MARL in the category of independent learner, are used to… read more here.
Keywords: optimization; cooperative tasks; reinforcement learning; multiagent reinforcement ... See more keywords
Hierarchical Multiagent Reinforcement Learning for Allocating Guaranteed Display Ads.
Sign Up to like & getrecommendations! Published in 2021 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2021.3070484
Abstract: In this article, we study the problem of guaranteed display ads (GDAs) allocation, which requires proactively allocate display ads to different impressions to fulfill their impression demands indicated in the contracts. Existing methods for this… read more here.
Keywords: display; guaranteed display; display ads; reinforcement learning ... See more keywords
UNMAS: Multiagent Reinforcement Learning for Unshaped Cooperative Scenarios.
Sign Up to like & getrecommendations! Published in 2021 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2021.3105869
Abstract: Multiagent reinforcement learning methods, such as VDN, QMIX, and QTRAN, that adopt centralized training with decentralized execution (CTDE) framework have shown promising results in cooperation and competition. However, in some multiagent scenarios, the number of… read more here.
Keywords: action value; action; multiagent reinforcement; reinforcement learning ... See more keywords
VGN: Value Decomposition With Graph Attention Networks for Multiagent Reinforcement Learning.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3172572
Abstract: Although value decomposition networks and the follow on value-based studies factorizes the joint reward function to individual reward functions for a kind of cooperative multiagent reinforcement problem, in which each agent has its local observation… read more here.
Keywords: decomposition graph; decomposition; value; value decomposition ... See more keywords