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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Reinforcement Learning From Hierarchical Critics
IEEE Transactions on Neural Networks and Learning Systems, 2023 This paper is submitted to IEEE ...
Zehong Cao, Chin-Teng Lin
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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
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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
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Hierarchical Reinforcement Learning Method Based on Trajectory Information [PDF]
Jisuanji kexue, 2023 The option-based hierarchical reinforcement learning(O-HRL) algorithm has the characteristics of temporal abstraction,which can effectively deal with complex problems such as long-term temporal order and sparse rewards that are difficult to solve in ...
XU Yapeng, LIU Quan, LI Junwei
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EarnHFT: Efficient Hierarchical Reinforcement Learning for High Frequency Trading [PDF]
AAAI Conference on Artificial Intelligence, 2023 High-frequency trading (HFT) is using computer algorithms to make trading decisions in short time scales (e.g., second-level), which is widely used in the Cryptocurrency (Crypto) market, (e.g., Bitcoin).
Molei Qin +5 more
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Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition [PDF]
Journal of Artificial Intelligence Research, 1999 This paper presents a new approach to hierarchical reinforcement learning based on decomposing the target Markov decision process (MDP) into a hierarchy of smaller MDPs and decomposing the value function of the target MDP into an additive combination of ...
Thomas G. Dietterich
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Hierarchical Reinforcement Learning for Precise Soccer Shooting Skills using a Quadrupedal Robot [PDF]
IEEE/RJS International Conference on Intelligent RObots and Systems, 2022 We address the problem of enabling quadrupedal robots to perform precise shooting skills in the real world using reinforcement learning. Developing algorithms to enable a legged robot to shoot a soccer ball to a given target is a challenging problem that
Yandong Ji +6 more
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Discrete Event Modeling and Simulation for Reinforcement Learning System Design
Information, 2022 Discrete event modeling and simulation and reinforcement learning are two frameworks suited for cyberphysical system design, which, when combined, can give powerful tools for system optimization or decision making process for example.
Laurent Capocchi +1 more
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Hierarchical Offset Object Detection Based on Human Visual Mechanism [PDF]
Jisuanji gongcheng, 2018 In order to solve the problem of low recall rate in object detection with the deep reinforcement learning method,on the basis of simulating human visual mechanism,a dynamic searching hierarchical offset method is proposed.It uses the idea of anchors ...
QIN Sheng,ZHANG Xiaolin,CHEN Lili,LI Jiamao
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