CityLearn v1.0: An OpenAI Gym Environment for Demand Response with Deep Reinforcement Learning. - José R. Vázquez-Canteli; Jérôme Henri Kämpf; Gregor Henze; Zoltán Nagy 002 (BuildSys, 2019)

MARLISA: Multi-Agent Reinforcement Learning with Iterative Sequential Action Selection for Load Shaping of Grid-Interactive Connected Buildings. - José R. Vázquez-Canteli; Gregor Henze; Zoltán Nagy 002 (BuildSys, 2020)

The CityLearn Challenge 2020. - José R. Vázquez-Canteli; Sourav Dey; Gregor Henze; Zoltán Nagy 002 (BuildSys, 2020)

CityLearn: Standardizing Research in Multi-Agent Reinforcement Learning for Demand Response and Urban Energy Management. - José R. Vázquez-Canteli; Sourav Dey; Gregor Henze; Zoltán Nagy 002 (CoRR, 2020)

The citylearn challenge 2021. - Zoltán Nagy 002; José R. Vázquez-Canteli; Sourav Dey; Gregor Henze (BuildSys, 2021)

IMPACT: Integrated Multi-Domain Emission Pathways For Cities Under Land-Use Policy, Technology Adoption, Climate Change And Grid Decarbonization. - Zoltán Nagy 002; Juliana Felkner; Ariane L. Beck; D. Cale Reeves; Steven Richter; Vivek Shastry; Eli Ramthun; Edward Mbata; Stephen Zigmund; Benjamin Marshall; Linnea Marks; Vianey Rueda; et al. (CoRR, 2022)