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A Reinforcement Learning Method for Automated Guided Vehicle Dispatching and Path Planning Considering Charging and Path Conflicts at an Automated Container Terminal

Journal of Marine Science and Engineering
The continued growth of international maritime trade has driven automated container terminals (ACTs) to pursue more efficient operational management strategies.
Tianli Zuo +5 more
doaj +1 more source

Cooperation Spectrum Sensing Detecting Algorithm Based on Featured Belief Points in Cognitive Radio Network

Dianxin kexue, 2013
In order to solve the dilemma of the tradeoff between spectrum sensing performance and spectrum sensing efficiency in cognitive radio network，a nove1 ED/FD cooperation spectrum sensing algorithm based on featured belief points was proposed.
Hongyan Zheng, Bo Wu, Yanpeng Feng, Xianjun Meng +3 more
doaj +2 more sources

Enhanced Multi-UAV Path Planning in Complex Environments With Voronoi-Based Obstacle Modelling and Q-Learning

International Journal of Aerospace Engineering
To tackle the challenge of obstacle avoidance path planning for multiple unmanned aerial vehicles (UAVs) in intricate environments, this study introduces a Voronoi graph–based model to represent the obstacle-laden environment and employs a Markov ...
Wenjia Su, Min Gao, Xinbao Gao, Zhaolong Xuan +3 more
doaj +1 more source

Multi-Agent Deep Reinforcement Learning for Large-Scale Traffic Signal Control with Spatio-Temporal Attention Mechanism

Applied Sciences
Traffic congestion in large-scale road networks significantly impacts urban sustainability. Traditional traffic signal control methods lack adaptability to dynamic traffic conditions. Recently, deep reinforcement learning (DRL) has emerged as a promising
Wenzhe Jia, Mingyu Ji
doaj +1 more source

A Comparative Analysis of Deep Reinforcement Learning-Enabled Freeway Decision-Making for Automated Vehicles

IEEE Access
In application, advanced autonomous driving technologies still face numerous challenges. Deep Reinforcement Learning (DRL) has emerged as a widespread and effective approach to address artificial intelligence challenges, due to its substantial potential ...
Teng Liu +4 more
doaj +1 more source

<html> Nash ε-equilibria for stochastic games with total reward functions: an approach through Markov decision processes</html> [PDF]

Kybernetika, 2019
Francisco J. González-Padilla, Raúl Montes-de-Oca +1 more
openaire +1 more source

Higher-Order Markov Model-Based Analysis of Reinforcement Learning in 6G Mobile Retrial Queueing Systems. [PDF]

Sensors (Basel)
Talbi D, Gal Z.
europepmc +1 more source

Adaptive Policy Switching for Multi-Agent ASVs in Multi-Objective Aquatic Cleaning Environments. [PDF]

Sensors (Basel)
Seck D +4 more
europepmc +1 more source

Active guidance in ultrasound bladder scanning using reinforcement learning. [PDF]

Sci Rep
Hsu HL +9 more
europepmc +1 more source

Optimizing genomic sampling for demographic and epidemiological inference with Markov decision processes. [PDF]

Genetics
Rasmussen DA, Bursell MG, Burkhart F.
europepmc +1 more source

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