[//]: # (Image References)

[image1]: https://user-images.githubusercontent.com/10624937/42135605-ba0e5f2c-7d12-11e8-9578-86d74e0976f8.gif "Trained Agent"

# Discretization

### Instructions

Follow the instructions in `Discretization.ipynb` to learn how to discretize continuous state spaces, to use tabular solution methods to solve complex tasks. The corresponding solutions can be found in `Discretization_Solution.ipynb`.

### Results

![Trained Agent][image1]

### Resources

To learn about more advanced discretization approaches, refer to the following:

- Uther, W., and Veloso, M., 1998. [Tree Based Discretization for Continuous State Space Reinforcement Learning](http://www.cs.cmu.edu/~mmv/papers/will-aaai98.pdf). In _Proceedings of AAAI, 1998_, pp. 769-774.
- Munos, R. and Moore, A., 2002. [Variable Resolution Discretization in Optimal Control](https://link.springer.com/content/pdf/10.1023%2FA%3A1017992615625.pdf). In _Machine Learning_, 49(2), pp. 291-323.
