Hierarchical Reinforcement Learning Framework in Geographic Coordination for Air Combat Tactical Pursuit [PDF]
Entropy, 2023 This paper proposes an air combat training framework based on hierarchical reinforcement learning to address the problem of non-convergence in training due to the curse of dimensionality caused by the large state space during air combat tactical pursuit.
Ruihai Chen +4 more
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A neural model of hierarchical reinforcement learning. [PDF]
PLoS ONE, 2017 We develop a novel, biologically detailed neural model of reinforcement learning (RL) processes in the brain. This model incorporates a broad range of biological features that pose challenges to neural RL, such as temporally extended action sequences ...
Daniel Rasmussen +2 more
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Hierarchical Reinforcement Learning: A Survey and Open Research Challenges
Machine Learning and Knowledge Extraction, 2022 Reinforcement learning (RL) allows an agent to solve sequential decision-making problems by interacting with an environment in a trial-and-error fashion. When these environments are very complex, pure random exploration of possible solutions often fails,
Matthias Hutsebaut-Buysse +2 more
doaj +2 more sources
Hierarchical reinforcement learning-based traffic signal control [PDF]
Scientific ReportsEfficient traffic light control is a critical issue in urban transportation systems. Recently, deep reinforcement learning (DRL) has gained popularity as a method for real-time traffic light control.
Jiajing Shen
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LLMs augmented hierarchical reinforcement learning with action primitives for long-horizon manipulation tasks [PDF]
Scientific ReportsDeep reinforcement learning methods have shown promising results in learning specific tasks, but struggle to cope with the challenges of long horizon manipulation tasks.
Ning Zhang +3 more
doaj +2 more sources
DT-HRL: Mastering Long-Sequence Manipulation with Reimagined Hierarchical Reinforcement Learning [PDF]
BiomimeticsRobotic manipulators in warehousing and logistics often face complex tasks that involve multiple steps, frequent task switching, and long-term dependencies. Inspired by the hierarchical structure of human motor control, this paper proposes a Hierarchical
Junyang Zhang +4 more
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Vision-Based Robot Navigation through Combining Unsupervised Learning and Hierarchical Reinforcement Learning [PDF]
Sensors, 2019 Extensive studies have shown that many animals’ capability of forming spatial representations for self-localization, path planning, and navigation relies on the functionalities of place and head-direction (HD) cells in the hippocampus.
Xiaomao Zhou +3 more
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Correction: Success-efficient/failure-safe strategy for hierarchical reinforcement motor learning. [PDF]
PLoS Computational Biology[This corrects the article DOI: 10.1371/journal.pcbi.1013089.].
PLOS Computational Biology Staff
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Applied Sciences, 2023 Deep reinforcement learning is one of the research hotspots in artificial intelligence and has been successfully applied in many research areas; however, the low training efficiency and high demand for samples are problems that limit the application ...
Rong Zhou, Zhisheng Zhang, Yuan Wang
doaj +1 more source
Hierarchical Reinforcement Learning Based Traffic Steering in Multi-RAT 5G Deployments [PDF]
ICC 2023 - IEEE International Conference on Communications, 2023 In 5G non-standalone mode, an intelligent traffic steering mechanism can vastly aid in ensuring a smooth user experience by selecting the best radio access technology (RAT) from a multi-RAT environment for a specific traffic flow.
Md Arafat Habib +7 more
semanticscholar +1 more source