
import numpy as np

import universe


seed = 91231
n_trials = 20
n_steps = 1000

steps_to_reward = 9
max_reward = n_steps // steps_to_reward * 5.

uni = universe.Universe('grid_world', world='2d_world0')
uni.show()

reward = []
for i in range(n_trials):
    np.random.seed(1234 + i)

    uni.reset_agent_position()
    uni.reset_agent_reward()
    for _ in range(n_steps):
        uni.step()

    reward.append(uni._agent._total_reward)
    print('total reward after {steps} steps: {reward}/{max_reward}'.format(steps=n_steps, reward=uni._agent._total_reward, max_reward=max_reward))


import matplotlib.pyplot as plt
import numpy as np

import universe


seed = 91231
n_trials = 20
n_steps = 1000

steps_to_reward = 14
max_reward = n_steps // steps_to_reward * 5.

uni = universe.Universe('grid_world', world='2d_world1')
uni.show()

reward = []
for i in range(n_trials):
    reward_trial = []
    np.random.seed(1234 + i)

    uni.reset_agent_position()
    uni.reset_agent_reward()
    for _ in range(n_steps):
        uni.step()

        reward_trial.append(uni._agent._total_reward)
    reward.append(reward_trial)
    print('total reward after {steps} steps: {reward}/{max_reward}'.format(steps=n_steps, reward=uni._agent._total_reward, max_reward=max_reward))


for i in range(n_trials):
    plt.plot(reward[i])
plt.show()

Add trial cumulative reward plot
Add trial cumulative reward plot

  
+ import matplotlib.pyplot as plt
  import numpy as np
  
  import universe
  
  
  seed = 91231
  n_trials = 20
  n_steps = 1000
  
- steps_to_reward = 9
+ steps_to_reward = 14
  max_reward = n_steps // steps_to_reward * 5.
  
- uni = universe.Universe('grid_world', world='2d_world0')
+ uni = universe.Universe('grid_world', world='2d_world1')
  uni.show()
  
  reward = []
  for i in range(n_trials):
+     reward_trial = []
      np.random.seed(1234 + i)
  
      uni.reset_agent_position()
      uni.reset_agent_reward()
      for _ in range(n_steps):
          uni.step()
  
-     reward.append(uni._agent._total_reward)
+         reward_trial.append(uni._agent._total_reward)
+     reward.append(reward_trial)
      print('total reward after {steps} steps: {reward}/{max_reward}'.format(steps=n_steps, reward=uni._agent._total_reward, max_reward=max_reward))
  
+ 
+ for i in range(n_trials):
+     plt.plot(reward[i])
+ plt.show()
+ 
Add trial cumulative reward plot
## Code Before:

import numpy as np

import universe


seed = 91231
n_trials = 20
n_steps = 1000

steps_to_reward = 9
max_reward = n_steps // steps_to_reward * 5.

uni = universe.Universe('grid_world', world='2d_world0')
uni.show()

reward = []
for i in range(n_trials):
    np.random.seed(1234 + i)

    uni.reset_agent_position()
    uni.reset_agent_reward()
    for _ in range(n_steps):
        uni.step()

    reward.append(uni._agent._total_reward)
    print('total reward after {steps} steps: {reward}/{max_reward}'.format(steps=n_steps, reward=uni._agent._total_reward, max_reward=max_reward))

## Instruction:
Add trial cumulative reward plot
## Code After:

import matplotlib.pyplot as plt
import numpy as np

import universe


seed = 91231
n_trials = 20
n_steps = 1000

steps_to_reward = 14
max_reward = n_steps // steps_to_reward * 5.

uni = universe.Universe('grid_world', world='2d_world1')
uni.show()

reward = []
for i in range(n_trials):
    reward_trial = []
    np.random.seed(1234 + i)

    uni.reset_agent_position()
    uni.reset_agent_reward()
    for _ in range(n_steps):
        uni.step()

        reward_trial.append(uni._agent._total_reward)
    reward.append(reward_trial)
    print('total reward after {steps} steps: {reward}/{max_reward}'.format(steps=n_steps, reward=uni._agent._total_reward, max_reward=max_reward))


for i in range(n_trials):
    plt.plot(reward[i])
plt.show()
