def main():
num_eps = 200000
agent = Agent()
env = Environment()
rlglue = RLGlue(env, agent)
del agent, env
solves = 0
rlglue.rl_init()
rewards = []
for ep in range(num_eps):
rlglue.rl_start()
#rlglue.rl_env_message('renderON')
terminal = False
reward = 0
while not terminal:
reward, state, action, terminal = rlglue.rl_step()
if ep > 1000:
rlglue.rl_env_message('renderON')
print(state)
time.sleep(0.1)
rewards.append(reward)
if ep >= 99:
if np.average(rewards[ep-99:ep+1]) > 0.78:
print('solved at episode %d' % ep+1)
break
else:
pass
def question_1():
# Specify hyper-parameters
agent = Agent()
environment = Environment()
rlglue = RLGlue(environment, agent)
np.random.seed(0)
num_episodes = 200
see_eps = [157]
num_runs = 1
max_eps_steps = 100000
# test with various stepsizes (alphas) for agent
stepSizes = np.linspace(0.01, 1, 100)
# best stepsize so far (comment out to test many)
stepSizes = [0.559184]
# seperate run for each stepsize
for step in stepSizes:
# initialize agent and software, with chosen stepsize
rlglue.rl_init()
rlglue.rl_agent_message('step:' + str(step))
# keep track of total rewards for each episode
total_rewards = []
for ep in range(num_episodes):
# render only selected episodes
if ep in see_eps:
rlglue.rl_env_message('rOFF')
if ep + 1 in see_eps:
rlglue.rl_env_message('rON')
print("Episode %d" % (ep + 1))
# initializse for episode
rlglue.rl_start()
terminal = False
total_reward = 0
# run episode and calculate total reward
while not terminal:
reward, state, action, terminal = rlglue.rl_step()
total_reward += reward
total_rewards.append(total_reward)
# calculate average reward of the last 100 episodes
if ep >= 99:
total = np.sum(total_rewards[ep - 99:ep + 1])
avg = total / 100
# check if results indicate the problem is solved
if avg > -110:
print("Solved at episode %d, avg reward: %f" %
(ep + 1, avg))
break
# close environment
environment.close()
def testPolicy(policy):
agent = testAgent(policy)
env = Environment()
rlglue = RLGlue(env, agent)
del env, agent
rlglue.rl_init()
for run in range(1):
rlglue.rl_init()
rlglue.rl_env_message('renderON')
rlglue.rl_start()
total_reward = 0
terminal = False
while not terminal:
r, s, a, terminal = rlglue.rl_step()
total_reward += r
return total_reward