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
-
DPG since
13.03.2023
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.
Core Components Assessed/Included Repositories
The following repositories were submitted by the solution and included in our evaluation. Any repositories, add-ons, features not included in here were not reviewed by us.
Feature
Scale of the Solution*
Connected members
N/A
Participated Programs
N/A
Available Languages
N/A
Organisations using it
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
Application Log Details
Timestamp
Activity
2025-11-05 17:22:02
System remove tag Late from CityLearn (12261)
2025-11-05 17:22:02
Bolaji Ayodeji (L1 Reviewer) submitted their review of CityLearn (12261)
2025-11-05 17:21:53
Bolaji Ayodeji (L1 Reviewer) passed Scale of Solution for CityLearn (12261)
2025-11-05 17:21:44
Bolaji Ayodeji (L1 Reviewer) passed 9C. Protection from Harassment for CityLearn (12261)
2025-11-05 17:21:31
Bolaji Ayodeji (L1 Reviewer) passed 9B. Inappropriate & Illegal Content for CityLearn (12261)
