Comparison of On-Policy Deep Reinforcement Learning A2C with Off-Policy DQN in Irrigation Optimization: A Case Study at a Site in Portugal

Comparison of On-Policy Deep Reinforcement Learning A2C with Off-Policy DQN in Irrigation Optimization: A Case Study at a Site in Portugal

Precision irrigation and optimization of water use have become essential factors in agriculture because water is critical for crop growth. The proper management of an irrigation system should enable the farmer to use water efficiently to increase productivity, reduce production costs, and maximize t...

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Bibliographic Details
Main Authors: Khadijeh Alibabaei, Pedro D. Gaspar, Eduardo Assunção, Saeid Alirezazadeh, Tânia M. Lima, Vasco N. G. J. Soares, João M. L. P. Caldeira
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Computers
Subjects:
agriculture
deep learning
on-policy deep reinforcement learning
irrigation optimization
Online Access:https://www.mdpi.com/2073-431X/11/7/104

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https://www.mdpi.com/2073-431X/11/7/104

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