def main():
with PuddleWorld(start=(0.5, 0.1), resolution=0.05) as world:
# R = PuddleReward(rmax=1.0, step_reward=0.1)
R = PuddleRewardLFA(weights=[1, -1], rmax=1.0)
T = PWTransition()
g = PuddleWorldMDP(reward=R, transition=T, discount=0.98)
# ------------------------
mdp_planner = PolicyIteration()
res = mdp_planner.solve(g)
V = res['V']
print(V)
print(res['pi'])
fig = plt.figure(figsize=(8, 8))
ax = fig.gca()
ax = world.visualize(ax, policy=res['pi'])
# plt.savefig('world.svg')
plt.figure(figsize=(8, 8))
plt.imshow(V.reshape(world.shape).T, # interpolation='nearest',
cmap='viridis', origin='lower',
vmin=np.min(V), vmax=np.max(V))
plt.grid(False)
plt.title('Value function')
plt.colorbar(orientation='horizontal')
# plt.savefig('world_value.svg')
plt.show()
def main():
NUM_STATES = 10
with ChainWorld(num_states=NUM_STATES) as world:
R = ChainReward()
T = ChainTransition()
mdp = ChainMDP(R, T, discount=0.98)
planner = PolicyIteration()
plan = planner.solve(mdp)
print(plan['pi'])
fig = plt.figure(figsize=(12, 3))
ax = fig.gca()
ax = world.visualize(ax)
ax = world.show_policy(ax, policy=plan['pi'])
plt.figure(figsize=(8, 8))
plt.plot(plan['V'])
plt.title('Value function')
plt.show()
