Modeling learning is the process of taking logged data and utilizing it to create a tool for predicting into the future. My work here started in the area of model-based reinforcement learning, but it is broad enough now that it warrants its own category. Model learning from batch data is also of great interest. If we can learn a useful model, we can leverage all the data we have logged to its fullest extent.
Predicting with a model into the future!
Open areas of study:
Models for long-term predictions,
Changing model training to prioritize task performance over accuracy,
2020 Conference on Learning for Decision and Control
Studying the numerical effects of a dual-optimization problem in model-based reinforcement learning -- control and dynamics. When optimizing model accuracy, there is no guarantee on improving task performance!
