# mud-games

control systems with MUD points

# installation

```bash
pip install -r requirements.txt
```


# usage

A `data.pkl` file is provided for your convenience with input / output samples.

The inputs are the parameters to a `4x1` matrix which is multiplied against the observations of the state in order to make a decision for the next action (push left or right). The output of the vector inner-product is binarized by comparison to zero as a threshold value.

The parameter space is standard normal.
There is no assumed error in observations, so the "data variance" is designed to reflect the acceptable ranges for the parameters:

From [gym](https://www.gymlibrary.ml/pages/environments/classic_control/cart_pole):
- The cart x-position (index 0) can be take values between (-4.8, 4.8), but the episode terminates if the cart leaves the (-2.4, 2.4) range.
- The pole angle can be observed between (-.418, .418) radians (or ±24°), but the episode terminates if the pole angle is not in the range (-.2095, .2095) (or ±12°)


The target "signal" is zero for all four dimensions of the observation space. The presumed "data variance" should actually correspond to the acceptable bands of signal (WIP).

```bash
python main.py
```

# generate data

You can generate your own data with:
```bash
python data.py
```

Note: if you change the presumed sample space in `data.py`, you should make the corresponding changes to the initial distribution in `main.py`.


# improvements

Using the following presumptions, we can establish better values for the "data variance":
The angular momentum of the pole is the most important thing to stabilize.