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Extracting a transferable rule-based controller from deep reinforcement learning agents with validation across multiple scenarios for heat pump systems with thermal storage
2026 Piscitelli, Marco Savino; Mele, Alessandro Aniello; Razzano, Giuseppe; Capozzoli, Alfonso
A scalable approach for real-world implementation of deep reinforcement learning controllers in buildings based on online transfer learning: The HiLo case study
2025 Coraci, Davide; Silvestri, Alberto; Razzano, Giuseppe; Fop, Davide; Brandi, Silvio; Borkowski, Esther; Hong, Tianzhen; Schlueter, Arno; Capozzoli, Alfonso
An interpretable data analytics-based energy benchmarking process for supporting retrofit decisions in large residential building stocks
2025 Piscitelli, Marco Savino; Razzano, Giuseppe; Buscemi, Giacomo; Capozzoli, Alfonso
Deploying deep reinforcement learning for low-level HVAC control in multi-zone buildings: A comparative study with ASHRAE G36 sequences
2025 Savino, Sabrina; Razzano, Giuseppe; Pagone, Michele; Novara, Carlo; Capozzoli, Alfonso
Rule extraction from deep reinforcement learning controller and comparative analysis with ASHRAE control sequences for the optimal management of Heating, Ventilation, and Air Conditioning (HVAC) systems in multizone buildings
2025 Razzano, Giuseppe; Brandi, Silvio; Piscitelli, Marco Savino; Capozzoli, Alfonso
| Citazione | Data di pubblicazione | Autori | File |
|---|---|---|---|
| Extracting a transferable rule-based controller from deep reinforcement learning agents with validation across multiple scenarios for heat pump systems with thermal storage / Piscitelli, M.S., Mele, A.A., Razzano, G., Capozzoli, A.. - In: APPLIED ENERGY. - ISSN 0306-2619. - 412:(2026). [10.1016/j.apenergy.2026.127661] | 1-gen-2026 | Piscitelli, Marco SavinoMele, Alessandro AnielloRazzano, GiuseppeCapozzoli, Alfonso | - |
| A scalable approach for real-world implementation of deep reinforcement learning controllers in buildings based on online transfer learning: The HiLo case study / Coraci, D., Silvestri, A., Razzano, G., Fop, D., Brandi, S., Borkowski, E., Hong, T., Schlueter, A., Capozzoli, A.. - In: ENERGY AND BUILDINGS. - ISSN 0378-7788. - 329:(2025). [10.1016/j.enbuild.2024.115254] | 1-gen-2025 | Davide CoraciGiuseppe RazzanoDavide FopSilvio BrandiAlfonso Capozzoli + | 1-s2.0-S0378778824013707-main.pdf |
| An interpretable data analytics-based energy benchmarking process for supporting retrofit decisions in large residential building stocks / Piscitelli, M.S., Razzano, G., Buscemi, G., Capozzoli, A.. - In: ENERGY AND BUILDINGS. - ISSN 0378-7788. - ELETTRONICO. - 328:(2025). [10.1016/j.enbuild.2024.115115] | 1-gen-2025 | Piscitelli, Marco SavinoRazzano, GiuseppeBuscemi, GiacomoCapozzoli, Alfonso | paper-main.pdf |
| Deploying deep reinforcement learning for low-level HVAC control in multi-zone buildings: A comparative study with ASHRAE G36 sequences / Savino, S., Razzano, G., Pagone, M., Novara, C., Capozzoli, A.. - In: ENERGY AND BUILDINGS. - ISSN 0378-7788. - 348:(2025). [10.1016/j.enbuild.2025.116456] | 1-gen-2025 | Savino, SabrinaRazzano, GiuseppePagone, MicheleNovara, CarloCapozzoli, Alfonso | 1-s2.0-S0378778825011867-main_compressed.pdf |
| Rule extraction from deep reinforcement learning controller and comparative analysis with ASHRAE control sequences for the optimal management of Heating, Ventilation, and Air Conditioning (HVAC) systems in multizone buildings / Razzano, G., Brandi, S., Piscitelli, M.S., Capozzoli, A.. - In: APPLIED ENERGY. - ISSN 0306-2619. - ELETTRONICO. - 381:(2025). [10.1016/j.apenergy.2024.125046] | 1-gen-2025 | Razzano, GiuseppeBrandi, SilvioPiscitelli, Marco SavinoCapozzoli, Alfonso | Manuscript APEN.pdf |