Bayesian Inverse Reinforcemen Learning

Paper URL: https://www.aaai.org/Papers/IJCAI/2007/IJCAI07-416.pdf

Enviornment is the figure1 in the birl paper

Tested on

python==3.7.0
numpy==1.15.1
scipy==1.1.0
tqdm==4.26.0
matplotlib==2.2.3

Run Experiments

python src/birl.py

Results

Sampled rewards for each states.
An optimal policy for mean of sampled rewards were exactly matched with the expert's policy.