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CityLearn
Official reinforcement learning environment for demand response and load shapingoccupant_centric_grid_interactive_buildings_course
ProfileClustering
CityDNN
Surrogate model using deep neural networks that allows estimating the heating and cooling loads of buildings at the urban scale.bevo_iaq
BEVO Beacon with more robust air quality monitoringSBC_course
DOE_XStock
dashboard
Dashboard showcasing Covid-19 research by the Intelligent Environments Lab at UT Austinbleed-orange-measure-purple
Data and Analysis related to the Bleed Orange, Measure Purple low-cost sensor project on UT's campusmerlin-apen-2023
occupancy_BT
IEL_GettingStarted
Guides for various topics to get started with research at IELrlem-workshop.net
RLEM brings together researchers and industry practitioners for the advancement of (deep) reinforcement learning (RL) in the built environment as it is applied for managing energy in civil infrastructure systems (energy, water, transportation).simbuild-2024-citylearn
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