6efe8ce53b30db7dd08dd727b23d6acb11796a8a,examples/grid_world.py,,,#,54

Before Change

    rewardQ1 = Parallel(n_jobs=-1)(
        delayed(experiment)(QLearning, 1) for _ in xrange(n_experiment))
    rewardQ08 = Parallel(n_jobs=-1)(
        delayed(experiment)(QLearning, .8) for _ in xrange(n_experiment))
    rewardDQ1 = Parallel(n_jobs=-1)(
        delayed(experiment)(DoubleQLearning, 1) for _ in xrange(n_experiment))
    rewardDQ08 = Parallel(n_jobs=-1)(

After Change

        for a in [QLearning, DoubleQLearning]:
            r = Parallel(n_jobs=-1)(
                delayed(experiment)(a, e) for _ in xrange(n_experiment))
            np.save("r" + names[a] + names[e] + ".npy", np.mean(r, axis=0))

Instances