Event submissions
Published
This submission belongs to the session S5. Agricultural Water Management of the event The 3rd International Online Conference on Agriculture
Published date
20 Oct, 2025
Academic Editor
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Antonio Paz-GonzalezCitation
Mohamed Abdelbaki, Jamal Ezzahar, Anouar Dalli, Saïd Khabba, Salah Er-Raki, Adnane Latif, Performance Assessment of DRL-Based Irrigation Agents in AquaCrop Using Local Data from Tensift Al Haouz: Toward Profit-Oriented Water Management, in Proceedings of The 3rd International Online Conference on Agriculture, 22 October–24 October 2025, MDPI: Basel, Switzerland
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Performance Assessment of DRL-Based Irrigation Agents in AquaCrop Using Local Data from Tensift Al Haouz: Toward Profit-Oriented Water Management
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Mohamed Abdelbaki 1
Jamal Ezzahar 2,3,4
Anouar Dalli 5
Saïd Khabba 3,4
Salah Er-Raki 6,7
Adnane Latif 1
1. TIM, ENSA, Université Cadi Ayyad, Marrakech, Morocco
2. LSA2D, École Supérieure de Technologie, El Kelaa Des Sraghna, Morocco
3. CRSA, Centre pour les Applications de la Télédétection, UM6P, Benguerir, Morocco
4. LMFE, Faculté des Sciences Semlalia, Université Cadi Ayyad, Marrakech, Morocco
5. École Nationale des Sciences Appliquées de Safi (ENSAS), Université Cadi Ayyad, Marrakech, Morocco
6. CRSA, Mohammed VI Polytechnic University, Ben Guerir, Morocco
7. CAB, Centre AgroBiotech-URL-CNRST-05, Cadi Ayyad University, Marrakech, Morocco
Abstract
Keywords
Irrigation Management
Deep Reinforcement Learning
Proximal Policy Optimization
AquaCrop