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  • Search: subject:"proximal policy optimization"
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Year of publication
Subject
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Learning 4 Lernen 4 Proximal policy optimization 4 Learning process 3 Lernprozess 3 Deep reinforcement learning 2 Theorie 2 Theory 2 proximal policy optimization 2 reinforcement learning 2 Air traffic management 1 Air transport 1 Airport 1 Backorders 1 Capacity planning 1 Dynamic pricing 1 Dynamic programming 1 Dynamische Optimierung 1 Flexible assembly 1 Flughafen 1 Image registration 1 Inventory control 1 Inventory model 1 Kapazitätsplanung 1 Lagerhaltungsmodell 1 Lagermanagement 1 Laser vision 1 Layout optimization 1 Luftverkehr 1 Mobile resources 1 Multi-agent deep reinforcement learning 1 Multi-echelon 1 Portfolio selection 1 Portfolio-Management 1 Preismanagement 1 Pricing strategy 1 Production control 1 Production scheduling 1 Queueing theory 1 Revenue management 1
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Online availability
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Undetermined 4 Free 2
Type of publication
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Article 6
Type of publication (narrower categories)
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Article in journal 4 Aufsatz in Zeitschrift 4 Article 1 research-article 1
Language
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English 6
Author
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Alam, Sameer 1 Andy, Lam Jun Guang 1 Chen, Yun 1 Garcia, Christopher 1 Geevers, Kevin 1 Göppert, Amon 1 Hezewijk, Lotte van 1 Huke, Philipp 1 Kaven, Lea 1 Li, Yaoming 1 Lilith, Nimrod 1 Mes, Martijn 1 Rajesh Piplani 1 Schmitt, Robert H. 1 Wenqing, Tan 1 Wu, Junfeng 1 Zhou, Hengchang 1 Zou, Yanbiao 1
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Published in...
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Central European journal of operations research 1 Industrial Robot: the international journal of robotics research and application 1 Journal of Intelligent Manufacturing 1 Journal of air transport management : a new international journal of research, policy and practice 1 Journal of business analytics 1 Journal of forecasting 1
Source
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ECONIS (ZBW) 4 EconStor 1 Other ZBW resources 1
Showing 1 - 6 of 6
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Multi agent reinforcement learning for online layout planning and scheduling in flexible assembly systems
Kaven, Lea; Huke, Philipp; Göppert, Amon; Schmitt, … - In: Journal of Intelligent Manufacturing 35 (2024) 8, pp. 3917-3936
policy optimization and consists of a decoder and encoder, allowing for various-sized system state descriptions. A simulation … scheduling in line-less mobile assembly systems. The proposed multi agent deep reinforcement learning algorithm uses proximal …
Persistent link: https://www.econbiz.de/10015371298
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Multi-echelon inventory optimization using deep reinforcement learning
Geevers, Kevin; Hezewijk, Lotte van; Mes, Martijn - In: Central European journal of operations research 32 (2024) 3, pp. 653-683
Persistent link: https://www.econbiz.de/10014582814
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Reinforcement learning for dynamic pricing and capacity allocation in monetized customer wait-skipping services
Garcia, Christopher - In: Journal of business analytics 8 (2025) 1, pp. 36-54
Persistent link: https://www.econbiz.de/10015188724
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Portfolio management based on a reinforcement learning framework
Wu, Junfeng; Li, Yaoming; Wenqing, Tan; Chen, Yun - In: Journal of forecasting 43 (2024) 7, pp. 2792-2808
Persistent link: https://www.econbiz.de/10015110562
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A deep reinforcement learning approach for Runway Configuration Management : a case study for Philadelphia International Airport
Andy, Lam Jun Guang; Alam, Sameer; Lilith, Nimrod; … - In: Journal of air transport management : a new … 120 (2024), pp. 1-15
Persistent link: https://www.econbiz.de/10015084639
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Laser vision seam tracking system based on proximal policy optimization
Zou, Yanbiao; Zhou, Hengchang - In: Industrial Robot: the international journal of robotics … 49 (2021) 4, pp. 770-778
Purpose This paper aims to propose a weld seam tracking method based on proximal policy optimization (PPO). Design …
Persistent link: https://www.econbiz.de/10014835831
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