Reward Shaping to Improve the Performance of Deep Reinforcement Learning in Inventory Management-Reference-Cited by-同舟云学术

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Reward Shaping to Improve the Performance of Deep Reinforcement Learning in Inventory Management

Published:2021 Issue: Volume: Page:
ISSN:1556-5068
Container-title:SSRN Electronic Journal
language:en
Short-container-title:SSRN Journal

Author:

De Moor Bram J.,Gijsbrechts Joren,Boute Robert N.

Publisher

Elsevier BV

Reference47 articles.

1. Deep reinforcement learning for inventory control: a roadmap;R N Boute;European Joural of Operational Research,2021

2. A heuristic to manage perishable inventory with batch ordering, positive lead-times, and time-varying demand;R A Broekmeulen;Computers & Operations Research,2009

3. Policy Transfer using Reward Shaping;T Brys;Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems,2015

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. AI in Logistics and Supply Chain Management;Global Logistics and Supply Chain Strategies for the 2020s;2022-12-09

2. Reward Shaping-based Double Deep Q-networks for Unmanned Surface Vessel Navigation and Obstacle Avoidance;IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society;2022-10-17

3. Deep reinforcement learning approach for solving joint pricing and inventory problem with reference price effects;Expert Systems with Applications;2022-06

4. Deep reinforcement learning for inventory control: A roadmap;European Journal of Operational Research;2022-04

5. AI in Logistics and Supply Chain Management;SSRN Electronic Journal;2021

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