Results 41 to 50 of about 57,740 (314)
Deep Reinforcement Learning for Inventory Control: A Roadmap [PDF]
SSRN Electronic Journal, 2021 Deep reinforcement learning (DRL) has shown great potential for sequential decision-making, including early developments in inventory control. Yet, the abundance of choices that come with designing a DRL algorithm, combined with the intense computational effort to tune and evaluate each choice, may hamper their application in practice.
Robert N. Boute +3 more
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Applied Artificial Intelligence, 2023 Nowadays, mobile robots are being widely employed in various settings, including factories, homes, and everyday tasks. Achieving successful implementation of autonomous robot movement largely depends on effective route planning.
Jieren Tan
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Agronomy, 2022 A series-parallel hybrid banana-harvesting robot was previously developed to pick bananas, with inverse kinematics intractable to an address. This paper investigates a deep reinforcement learning-based inverse kinematics solution to guide the banana ...
Guichao Lin +5 more
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Transfer Learning in Deep Reinforcement Learning: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 Reinforcement learning is a learning paradigm for solving sequential decision-making problems. Recent years have witnessed remarkable progress in reinforcement learning upon the fast development of deep neural networks. Along with the promising prospects of reinforcement learning in numerous domains such as robotics and game-playing, transfer learning ...
Zhuangdi Zhu +3 more
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Improvement of Deep Reinforcement Learning Using Curriculum in Game Environment
مجله پژوهش در علوم توانبخشی, 2020 Introduction: Training deep curriculum learning is a kind of smart agent training in which, first the simple acts, and then, the difficult acts are trained to smart agent.
Mohammadreza Mohammadnejad +2 more
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Deep Reinforcement Learning [PDF]
, 2019 Die Interaktion mit der umgebenden Welt kann als eine Grundlage des menschlichen Lernens betrachtet werden [93]. Kinder, welche die notigen motorischen Ablaufe zum Besteigen einer Treppe erlernen, haben dafur keinen direkten Lehrer. Stattdessen erarbeiten sie sich die entsprechenden Bewegungsablaufe durch Fehlschlage und Erfolge, durch das Studieren ...
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Body Language Analysis Based on Deep Reinforcement Learning [PDF]
ITM Web of ConferencesDeep learning has become one of the core technologies in current artificial intelligence research and application and has triggered revolutionary breakthroughs in many fields, demonstrating powerful learning ability and creativity.
Lu Boyang
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Routing algorithms as tools for integrating social distancing with emergency evacuation
Scientific Reports, 2021 One of the lessons from the COVID-19 pandemic is the importance of social distancing, even in challenging circumstances such as pre-hurricane evacuation. To explore the implications of integrating social distancing with evacuation operations, we describe
Yi-Lin Tsai +3 more
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Deep reinforcement learning for imbalanced classification [PDF]
Applied Intelligence, 2020 Data in real-world application often exhibit skewed class distribution which poses an intense challenge for machine learning. Conventional classification algorithms are not effective in the case of imbalanced data distribution, and may fail when the data distribution is highly imbalanced.
Qi Xiaoming, Chen Qiong, Enlu Lin
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Applied Sciences, 2022 In recent years, the recommendation system and robot learning are undoubtedly the two most popular application fields, and the core algorithms supporting these two fields are deep learning based on perception and reinforcement learning based on ...
Huaidong Yu, Jian Yin
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