Using Meta Reinforcement Learning to Bridge the Gap between Simulation and Experiment in Energy Demand Response.
Doseok JangLucas SpangherManan KhattarUtkarsha AgwanCostas J. SpanosPublished in: CoRR (2021)
Keyphrases
- reinforcement learning
- total energy
- simulation models
- simulation model
- simulation study
- energy consumption
- function approximation
- dynamic programming
- low energy
- neural network
- mathematical model
- markov decision processes
- optimal policy
- energy minimization
- supply chain
- optimal control
- meta level
- reinforcement learning algorithms
- inventory control