CityLearn: Standardizing Research in Multi-Agent Reinforcement Learning
for Demand Response and Urban Energy Management

CityLearn: Standardizing Research in Multi-Agent Reinforcement Learning for Demand Response and Urban Energy Management

18 December 2020

José R. Vázquez-Canteli

Papers citing "CityLearn: Standardizing Research in Multi-Agent Reinforcement Learning for Demand Response and Urban Energy Management"

19 / 19 papers shown

Title
RL2Grid: Benchmarking Reinforcement Learning in Power Grid Operations Enrico Marchesini Benjamin Donnot Constance Crozier Ian Dytham Christian Merz Lars Schewe Nico Westerbeck Cathy Wu Antoine Marot P. Donti OffRL 59 1 0 29 Mar 2025
Optimization Solution Functions as Deterministic Policies for Offline Reinforcement Learning Vanshaj Khattar Ming Jin OffRL 23 0 0 27 Aug 2024
A Novel Bifurcation Method for Observation Perturbation Attacks on Reinforcement Learning Agents: Load Altering Attacks on a Cyber Physical Power System Kiernan Broda-Milian Ranwa Al-Mallah H. Dagdougui AAML 51 0 0 06 Jul 2024
EVLearn: Extending the CityLearn Framework with Electric Vehicle Simulation Tiago Fonseca Luis Lino Ferreira Bernardo Cabral Ricardo Severino Kingsley Nweye Dipanjan Ghose Zoltán Nagy 27 3 0 08 Apr 2024
EnergAIze: Multi Agent Deep Deterministic Policy Gradient for Vehicle to Grid Energy Management Tiago Fonseca Luis Lino Ferreira Bernardo Cabral Ricardo Severino Isabel Praça 20 2 0 02 Apr 2024
Application-Driven Innovation in Machine Learning David Rolnick Alán Aspuru-Guzik Sara Beery B. Dilkina P. Donti ... Hannah Kerner C. Monteleoni Esther Rolf Milind Tambe Adam White 41 8 0 26 Mar 2024
Adaptive Control of Resource Flow to Optimize Construction Work and Cash Flow via Online Deep Reinforcement Learning Can Jiang Xin Li Jianpeng Lin Ming Liu Zhiliang Ma AI4CE 22 19 0 20 Jul 2023
Federated Ensemble-Directed Offline Reinforcement Learning Desik Rengarajan N. Ragothaman D. Kalathil S. Shakkottai OffRL 35 1 0 04 May 2023
Off-the-Grid MARL: Datasets with Baselines for Offline Multi-Agent Reinforcement Learning Claude Formanek Asad Jeewa Jonathan P. Shock Arnu Pretorius OffRL 43 2 0 01 Feb 2023
A Survey of Meta-Reinforcement Learning Jacob Beck Risto Vuorio E. Liu Zheng Xiong L. Zintgraf Chelsea Finn Shimon Whiteson OOD OffRL 42 125 0 19 Jan 2023
Multi-Agent Reinforcement Learning for Fast-Timescale Demand Response of Residential Loads Vincent Mai Philippe Maisonneuve Tianyu Zhang Hadi Nekoei Liam Paull Antoine Lesage-Landry AI4CE 23 5 0 06 Jan 2023
MERLIN: Multi-agent offline and transfer learning for occupant-centric energy flexible operation of grid-interactive communities using smart meter data and CityLearn Kingsley Nweye S. Sankaranarayanan Zoltán Nagy OffRL AI4CE 30 25 0 31 Dec 2022
Winning the CityLearn Challenge: Adaptive Optimization with Evolutionary Search under Trajectory-based Guidance Vanshaj Khattar Ming Jin 26 12 0 04 Dec 2022
BEAR: Physics-Principled Building Environment for Control and Reinforcement Learning Chi Zhang Yu Shi Yize Chen 16 6 0 27 Nov 2022
B2RL: An open-source Dataset for Building Batch Reinforcement Learning Hsin-Yu Liu Xiaohan Fu Bharathan Balaji Rajesh E. Gupta Dezhi Hong OffRL 27 4 0 30 Sep 2022
Performance Comparison of Deep RL Algorithms for Energy Systems Optimal Scheduling Shengren Hou Edgar Mauricio Salazar Duque Pedro P. Vergara Peter Palensky 19 16 0 01 Aug 2022
Real-world challenges for multi-agent reinforcement learning in grid-interactive buildings Kingsley Nweye Bo Liu Peter Stone Zoltán Nagy OffRL AI4CE 37 37 0 25 Nov 2021
PowerGridworld: A Framework for Multi-Agent Reinforcement Learning in Power Systems David J. Biagioni Xinming Zhang Dylan Wald Deepthi Vaidhynathan Rohit Chintala J. King Ahmed S. Zamzam 35 32 0 10 Nov 2021
GridLearn: Multiagent Reinforcement Learning for Grid-Aware Building Energy Management Aisling Pigott Constance Crozier K. Baker Zoltán Nagy AI4CE 79 39 0 12 Oct 2021