Reinforcement Learning Methods
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Currently there are no reinforcement learning methods implemented for forecast-based controllers. Feel free to expand the framework with your own reinforcement learning forecast-based controllers!

Potential approaches for reinforcement learning forecast-based controllers could include:

- Deep reinforcement learning with forecast information as part of the state
- Recurrent neural networks that process forecast sequences
- Model-based reinforcement learning that incorporates forecast models
- Multi-agent reinforcement learning for coordinating multiple energy resources based on forecasts

If you implement a reinforcement learning forecast-based controller, consider contributing it back to the HAMLET project.