Michael Pilosov
45ce364166
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3 years ago | |
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.gitignore | 3 years ago | |
README.md | 3 years ago | |
data.pkl | 3 years ago | |
main.py | 3 years ago | |
requirements.txt | 3 years ago | |
sample.py | 3 years ago |
README.md
mud-games
control systems with MUD points
installation
pip install -r requirements.txt
usage
A data.pkl
file is provided for your convenience with input / output samples.
python main.py
info
The inputs are the parameters to a 1x4
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 comparing it to zero as a threshold value.
The parameter space is standard normal. There is no assumed error in observations; the "data variance" is designed to reflect the acceptable ranges for the parameters:
From gym:
- 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°)
Therefore, since our objective is to stabilize the cart, the target "time series 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).
generate data
You can generate your own data with:
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.