Building control system using reinforcement learning

A method for generating a prediction model for control of a building management system, comprising:

• determining, by a processing circuit, policy rankings for a plurality of control policies based on building operation data of a first previous time period;
• selecting, by the processing circuit, a set of control policies from among the plurality of control policies based on the policy rankings of the set of control policies satisfying a ranking threshold;
• generating, by the processing circuit, a plurality of prediction models for the set of control policies;
• selecting, by the processing circuit, a first prediction model of the plurality of prediction models based on building operation data of a second previous time period;
• and
• responsive to selecting the first prediction model, operating, by the processing circuit, the building management system using the first prediction model.

A building management system, comprising:

• building equipment operatively connected to one or more processors;
• and
• one or more memory devices configured to store instructions thereon that, when executed by the one or more processors, cause the one or more processors to:
• determine policy rankings for a plurality of control policies based on building operation data of a first previous time period;
• select a set of control policies from among the plurality of control policies based on the policy rankings of the set of control policies satisfying a ranking thresh old;
• generate a plurality of prediction models for the set of control policies;
• select a first prediction model of the plurality of prediction models based on building operation data of a second previous time period;
• and
• responsive to selecting the first prediction model, operate the building equipment using the first prediction model.