| Quantifying the impact of US electric vehicle sales on light-duty vehicle fleet CO2 emissions using a novel agent-based simulation L Spangher, W Gorman, G Bauer, Y Xu, C Atkinson Transportation Research Part D: Transport and Environment 72, 358-377, 2019 | 39 | 2019 |
| Augmenting reinforcement learning with a planning model for optimizing energy demand response L Spangher, A Gokul, M Khattar, J Palakapilly, U Agwan, A Tawade, ... Proceedings of the 1st International Workshop on Reinforcement Learning for …, 2020 | 15 | 2020 |
| Offline-online reinforcement learning for energy pricing in office demand response: lowering energy and data costs D Jang, L Spangher, T Srivistava, M Khattar, U Agwan, S Nadarajah, ... Proceedings of the 8th ACM International Conference on Systems for Energy …, 2021 | 14 | 2021 |
| Prospective experiment for reinforcement learning on demand response in a social game framework L Spangher, A Gokul, M Khattar, J Palakapilly, A Tawade, A Bouyamourn, ... Proceedings of the Eleventh ACM International Conference on Future Energy …, 2020 | 13 | 2020 |
| Engineering vs. ambient type visualizations: Quantifying effects of different data visualizations on energy consumption L Spangher, A Tawade, A Devonport, C Spanos Proceedings of the 1st ACM International Workshop on Urban Building Energy …, 2019 | 13 | 2019 |
| Characterizing fusion market entry via an agent-based power plant fleet model L Spangher, JS Vitter, R Umstattd Energy Strategy Reviews 26, 100404, 2019 | 13 | 2019 |
| Pricing in prosumer aggregations using reinforcement learning U Agwan, L Spangher, W Arnold, T Srivastava, K Poolla, CJ Spanos Proceedings of the Twelfth ACM International Conference on Future Energy …, 2021 | 12 | 2021 |
| Using meta reinforcement learning to bridge the gap between simulation and experiment in energy demand response D Jang, L Spangher, M Khattar, U Agwan, C Spanos Proceedings of the Twelfth ACM International Conference on Future Energy …, 2021 | 9 | 2021 |
| Deep reinforcement learning with planning guardrails for building energy demand response D Jang, L Spangher, S Nadarajah, C Spanos Energy and AI 11, 100204, 2023 | 8 | 2023 |
| Adapting surprise minimizing reinforcement learning techniques for transactive control W Arnold, T Srivastava, L Spangher, U Agwan, C Spanos Proceedings of the Twelfth ACM International Conference on Future Energy …, 2021 | 8 | 2021 |
| Officelearn: An openai gym environment for reinforcement learning on occupant-level building’s energy demand response L Spangher, A Gokul, J Palakapilly, U Agwan, M Khattar, WJ Ma, ... Tackling Climate Change with Artificial Intelligence Workshop at NeurIPS 2020, 2020 | 7 | 2020 |
| Decarbonizing buildings via energy demand response and deep reinforcement learning: The deployment value of supervisory planning and guardrails D Jang, L Spangher, S Nadarajah, C Spanos Available at SSRN 4078206, 2022 | 6 | 2022 |
| Machine learning for smart and energy-efficient buildings HP Das, YW Lin, U Agwan, L Spangher, A Devonport, Y Yang, J Drgoňa, ... Environmental Data Science 3, e1, 2024 | 5 | 2024 |
| Adversarial poisoning attacks on reinforcement learning-driven energy pricing S Gunn, D Jang, O Paradise, L Spangher, CJ Spanos Proceedings of the 9th ACM International Conference on Systems for Energy …, 2022 | 4 | 2022 |
| Transactive multi-agent reinforcement learning for distributed energy price localization L Spangher Proceedings of the 8th ACM International Conference on Systems for Energy …, 2021 | 4 | 2021 |
| Continuous convolutional neural networks for disruption prediction in nuclear fusion plasmas WF Arnold, L Spangher, C Rea arXiv preprint arXiv:2312.01286, 2023 | 2 | 2023 |
| Personalized Federated Hypernetworks for Privacy Preservation in Multi-Task Reinforcement Learning D Jang, L Yan, L Spangher, CJ Spanos arXiv preprint arXiv:2210.06820, 2022 | 2 | 2022 |
| Active Reinforcement Learning for Robust Building Control D Jang, L Yan, L Spangher, CJ Spanos Proceedings of the AAAI Conference on Artificial Intelligence 38 (20), 22150 …, 2024 | 1 | 2024 |
| Personalized Federated Hypernetworks for Multi-Task Reinforcement Learning in Microgrid Energy Demand Response D Jang, L Spangher, T Srivastava, L Yan, C Spanos Proceedings of the 10th ACM International Conference on Systems for Energy …, 2023 | 1 | 2023 |
| Autoregressive Transformers for Disruption Prediction in Nuclear Fusion Plasmas L Spangher, W Arnold, A Spangher, A Maris, C Rea arXiv preprint arXiv:2401.00051, 2023 | | 2023 |
Costas SpanosProfessor of Electrical Engineering and Computer Sciences, University of California, BerkeleyVerifierad e-postadress på berkeley.edu
