Presentation on the paper: "A Methodology Based on Deep Q-Learning for Optimizing COVID-19 Pandemic Government Actions"


Presentation on how to apply Reinforcement Learning to fight the COVID-19 Pandemic in Mexico


Confinement levels optimization applied to Mexico:

Overview about Reinforcement Learning


This video gives an overview on Reinforcement Learning:

Highlighted Publications until 2021


  • Multi-objective evolutionary feature selection for online sales forecasting (2017) F Jiménez, G Sánchez, JM García, G Sciavicco, L Miralles. Neurocomputing 234, 75-92
  • A novel wearable sensor-based human activity recognition approach using artificial hydrocarbon networks (2016) H Ponce, MDL Martínez-Villaseñor, L Miralles-Pechuán Sensors 16 (7), 1033
  • A flexible approach for human activity recognition using artificial hydrocarbon networks (2016) H Ponce, L Miralles-Pechuán, MDL Martínez-Villaseñor. Sensors 16 (11), 1715
  • A methodology based on Deep Learning for advert value calculation in CPM, CPC and CPA networks (2017) L Miralles-Pechuán, D Rosso, F Jiménez, JM García. Soft Computing 21 (3), 651-665
  • A novel methodology for optimizing display advertising campaigns using genetic algorithms (2018) L Miralles-Pechuán, H Ponce, L Martínez-Villaseñor Electronic Commerce Research and Applications 27, 39-51 
  • Artificial hydrocarbon networks for online sales prediction (2015) H Ponce, L Miralles-Pechúan, M de Lourdes Martínez-Villaseñor. Mexican international conference on artificial intelligence, 498-508
  • Cutting through the emissions: feature selection from electromagnetic side-channel data for activity detection (2020) A Sayakkara, L Miralles-Pechuán, NA Le-Khac, M Scanlon. Forensic Science International: Digital Investigation 32, 300927
  • Comparative analysis of artificial hydrocarbon networks and data-driven approaches for human activity recognition (2015) H Ponce, M de Lourdes Martínez-Villaseñor, L Miralles-Pechúan. International conference on ubiquitous computing and ambient intelligence.
  • A Deep Q-learning/genetic Algorithms Based Novel Methodology For Optimizing Covid-19 Pandemic Government Actions(2020) L Miralles-Pechuán, F Jiménez, H Ponce, L Martínez-Villaseñor arXiv preprint arXiv:2005.07656
  • An overview of deep learning in industry (2020). Q Le, L Miralles-Pechuán, S Kulkarni, J Su, O Boydell. Data Analytics and AI, 65-98
  • Multi-Objective Evolutionary Rule-Based Classification with Categorical Data (2018)
  • F Jiménez, C Martínez, L Miralles-Pechuán, G Sánchez, G Sciavicco. Entropy 20 (9), 684
  • Optimization of the Containment Levels for the Reopening of Mexico City due to COVID-19 (2021). L Miralles-Pechuan, H Ponce, L Martinez-Villasenor. IEEE Latin America Transactions 19 (6), 1065-1073
  • A methodology based on deep q-learning/genetic algorithms for optimizing covid-19 pandemic government actions (2020). L Miralles-Pechuán, F Jiménez, H Ponce, L Martínez-Villaseñor. Proceedings of the 29th ACM International Conference on Information