From ead894881e9ad40ef711f5872c25e57c74311eaf Mon Sep 17 00:00:00 2001
From: Erik Nygren <erik.nygren@sbb.ch>
Date: Wed, 22 May 2019 17:47:52 +0200
Subject: [PATCH] Minor fixes in training_navigation.py
---
examples/training_navigation.py | 28 +++++++---------------------
1 file changed, 7 insertions(+), 21 deletions(-)
diff --git a/examples/training_navigation.py b/examples/training_navigation.py
index 85f9531b..4c8f15f7 100644
--- a/examples/training_navigation.py
+++ b/examples/training_navigation.py
@@ -36,7 +36,7 @@ env = RailEnv(width=20,
"""
env = RailEnv(width=15,
height=15,
- rail_generator=complex_rail_generator(nr_start_goal=2, nr_extra=30, min_dist=5, max_dist=99999, seed=0),
+ rail_generator=complex_rail_generator(nr_start_goal=6, nr_extra=30, min_dist=10, max_dist=99999, seed=0),
number_of_agents=3)
"""
@@ -144,8 +144,8 @@ for trials in range(1, n_trials + 1):
# Run episode
for step in range(100):
if demo:
- env_renderer.renderEnv(show=True, obsrender=True)
- time.sleep(2)
+ env_renderer.renderEnv(show=True)
+
# print(step)
# Action
for a in range(env.get_num_agents()):
@@ -193,29 +193,15 @@ for trials in range(1, n_trials + 1):
scores.append(np.mean(scores_window))
dones_list.append((np.mean(done_window)))
- print(
- '\rTraining {} Agents.\t' +
- 'Episode {}\t' +
- 'Average Score: {:.0f}\t' +
- 'Dones: {:.2f}%\t' +
- 'Epsilon: {:.2f} \t ' +
- 'Action Probabilities: \t ' +
- '{}'.format(
+ print('\rTraining {} Agents.\t Episode {}\t Average Score: {:.0f}\tDones: {:.2f}%\tEpsilon: {:.2f} \t Action Probabilities: \t {}'.format(
env.get_num_agents(),
trials,
np.mean(scores_window),
100 * np.mean(done_window),
- eps, action_prob / np.sum(action_prob)),
- end=" ")
+ eps, action_prob / np.sum(action_prob)), end=" ")
+
if trials % 100 == 0:
- print(
- '\rTraining {} Agents.\t' +
- 'Episode {}\t' +
- 'Average Score: {:.0f}\t' +
- 'Dones: {:.2f}%\t' +
- 'Epsilon: {:.2f} \t ' +
- 'Action Probabilities: \t ' +
- '{}'.format(
+ print('\rTraining {} Agents.\t Episode {}\t Average Score: {:.0f}\tDones: {:.2f}%\tEpsilon: {:.2f} \t Action Probabilities: \t {}'.format(
env.get_num_agents(),
trials,
np.mean(scores_window),
--
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