Snippet for toyCarIRL, blog usage, not executable

toyCarIRL6.py

if __name__ == '__main__':
    logger = logging.getLogger()
    logger.setLevel(logging.INFO)
    randomPolicyFE = [ 7.74363107 , 4.83296402 , 6.1289194  , 0.39292849 , 2.0488831  , 0.65611318 , 6.90207523 , 2.46475348]
    # ^the random policy feature expectations
    expertPolicyYellowFE = [7.5366e+00,  4.6350e+00  , 7.4421e+00, 3.1817e-01,  8.3398e+00,  1.3710e-08,  1.3419e+00 ,  0.0000e+00]
    # ^feature expectations for the "follow Yellow obstacles" behavior
    expertPolicyRedFE = [7.9100e+00, 5.3745e-01,  5.2363e+00, 2.8652e+00,  3.3120e+00, 3.6478e-06, 3.82276074e+00  , 1.0219e-17] 
    # ^feature expectations for the follow Red obstacles behavior
    expertPolicyBrownFE = [5.2210e+00,  5.6980e+00,  7.7984e+00,  4.8440e-01, 2.0885e-04, 9.2215e+00, 2.9386e-01 , 4.8498e-17]
    # ^feature expectations for the "follow Brown obstacles" behavior
    expertPolicyBumpingFE = [  7.5313e+00, 8.2716e+00, 8.0021e+00, 2.5849e-03 ,2.4300e+01 ,9.5962e+01 ,1.5814e+01 ,1.5538e+03]
    # ^feature expectations for the "nasty bumping" behavior
    epsilon = 0.1
    irlearner = irlAgent(randomPolicyFE, expertPolicyRedFE, epsilon, NUM_STATES, FRAMES, BEHAVIOR)
    print (irlearner.optimalWeightFinder())