Environments for the Statistical Reinforcement Learning project
Project description
Statistical Reinforcement Learning Environments
Environments for Statistical Reinforcement Learning
Installation
pip install statisticalRL-environments
Test
python fulldemo.py
List of environments:
MABS:
mab-bernoulli
MDPs:
random-rich
ergodic-random-rich
random-12
random-small
random-small-sparse
random-100
three-state
nasty
river-swim-6
ergo-river-swim-6
ergo-river-swim-25
river-swim-25
GRIDWORLD MDPs:
grid-random-1616
grid-random-1212
grid-random-88
grid-2-room
grid-4-room
The library contains several stochastic MDPs, that is for which transition and reward functions are not deterministic.
Randomly generated environments:
Furthermore, the library supports random generations of MDPs. The environments containing "random" in their name are randomly generated MDPs, that is with randomly generated transition and reward (stochastic) functions. For reproducibility reasons, they are generated with a given seed.
You can modify them in the registration list "registerStatisticalRLenvironments" available in the init file of lib. In this list, you will find environments registered with specific parameters, including the (last) parameter "seed" which is used to generate the random transition and reward functions.
"random-small" : lambda x: registerRandomMDP(nbStates=3, nbActions=4, maxProportionSupportTransition=0.5, maxProportionSupportReward=0.4, maxProportionSupportStart=0.1, minNonZeroProbability=0.15, minNonZeroReward=0.25, rewardStd=0.1,seed=5),
Note: fixing this seed (here sedd=5) does not prevent the transitions/rewards to be stochastic, as they are using another random number generating process.
Rendering
Each type of environment comes with different renderers, including the null renderer that displays nothing.
Text rendering:
This rendering is available for all environment types.
MAB Text rendering:
MDP Text rendering:
Gridworld-MDP Text rendering
Graph rendering:
This rendering is available for MDPs. On top of the visual display, it captures a screenshot png at each time step. This may be slow for large MDPs.
Grid-world rendering:
This rendering is available for Gridworld-MDPs. On top of the visual display, it captures a screenshot png at each time step.
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