Results 11 to 20 of about 387,064 (296)
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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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 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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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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3D reconstruction based on hierarchical reinforcement learning with transferability
Integr. Comput. Aided Eng., 2023 3D reconstruction is extremely important in CAD (computer-aided design)/CAE (computer-aided Engineering)/CAM (computer-aided manufacturing). For interpretability, reinforcement learning (RL) is used to reconstruct 3D shapes from images by a series of ...
Lan Li +4 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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IEEE Access, 2022 Military vehicle object detection technology in complex environments is the basis for the implementation of reconnaissance and tracking tasks for weapons and equipment, and is of great significance for information and intelligent combat.
Yan Ouyang +4 more
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HLifeRL: A hierarchical lifelong reinforcement learning framework
Journal of King Saud University: Computer and Information Sciences, 2022 Deep reinforcement learning research in a single-task environment has made remarkable achievements. However, it is often plagued by catastrophic forgetting, prohibitively low sample efficiency and lack of scalability problems when facing multi-task ...
Fan Ding, Fei Zhu
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