CityLearn
Verified DPG
Owner
Jose Ramon Vazquez-Canteli, Kingsley Nweye, Zoltan Nagy
Type
desktop
Licence
MIT
Last evaluated
22.03.2024
Origin country
United States of America
contact
nagy@utexas.eduRelease date
-
Description
CityLearn is an open source OpenAI Gym environment for the implementation of advanced control systems, e.g., MPC, and Multi-Agent Reinforcement Learning (RL) for building energy coordination and demand response in several buildings. CityLearn allows easy implementation agents in a multi-agent setting to reshape their aggregated curve of electrical demand.
Feature
Scale of the Solution*
Connected members
N/A
Participated Programs
N/A
Organisations using it
N/A
Available Languages
N/A
* This information is self-reported and updated annually
Github insights
Learn how this product has met the requirements of the DPG Standard by exploring the indicators below.
Application Details
DPG ID
GID0090321
Status
DPG
Date Created
2024-03-12
Date Submitted
2024-03-12
Date Reviewed
2024-03-22
Date of Expiry
2025-03-22
Application Log Details
Timestamp
Activity
2024-03-22 12:28:57
Richard Kagaba (L2 Reviewer) submitted their review of CityLearn (1051) and found it to be a DPG
2024-03-22 12:28:55
System unmarked CityLearn (11399) as a nominee
2024-03-22 12:28:44
Richard Kagaba (L2 Reviewer) passed Scale of Solution for CityLearn (11399)
2024-03-22 12:28:38
Richard Kagaba (L2 Reviewer) passed 9C. Protection from Harassment for CityLearn (11399)
2024-03-22 12:28:32
Richard Kagaba (L2 Reviewer) passed 9B. Inappropriate & Illegal Content for CityLearn (11399)