From 48eb6c32668cdee4a91d99f83cd6a81451a67cea Mon Sep 17 00:00:00 2001
From: MLErik <baerenjesus@gmail.com>
Date: Sat, 10 Aug 2019 16:58:38 -0400
Subject: [PATCH] minor updates
---
examples/training_example.py | 8 ++++----
1 file changed, 4 insertions(+), 4 deletions(-)
diff --git a/examples/training_example.py b/examples/training_example.py
index 69104613..70986c55 100644
--- a/examples/training_example.py
+++ b/examples/training_example.py
@@ -14,11 +14,12 @@ np.random.seed(1)
TreeObservation = TreeObsForRailEnv(max_depth=2, predictor=ShortestPathPredictorForRailEnv())
LocalGridObs = LocalObsForRailEnv(view_height=10, view_width=2, center=2)
+
env = RailEnv(width=50,
height=50,
rail_generator=complex_rail_generator(nr_start_goal=20, nr_extra=1, min_dist=8, max_dist=99999, seed=0),
obs_builder_object=TreeObservation,
- number_of_agents=20)
+ number_of_agents=10)
env_renderer = RenderTool(env, gl="PILSVG", )
@@ -58,7 +59,7 @@ class RandomAgent:
# Initialize the agent with the parameters corresponding to the environment and observation_builder
-agent = RandomAgent(218, 4)
+agent = RandomAgent(218, 5)
n_trials = 5
# Empty dictionary for all agent action
@@ -75,7 +76,7 @@ for trials in range(1, n_trials + 1):
score = 0
# Run episode
- for step in range(100):
+ for step in range(500):
# Chose an action for each agent in the environment
for a in range(env.get_num_agents()):
action = agent.act(obs[a])
@@ -89,7 +90,6 @@ for trials in range(1, n_trials + 1):
for a in range(env.get_num_agents()):
agent.step((obs[a], action_dict[a], all_rewards[a], next_obs[a], done[a]))
score += all_rewards[a]
-
obs = next_obs.copy()
if done['__all__']:
break
--
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