From ffa48c3b035181a6ca565ac261b4e83a58502112 Mon Sep 17 00:00:00 2001
From: Erik Nygren <erik.nygren@sbb.ch>
Date: Fri, 14 Jun 2019 01:14:02 +0200
Subject: [PATCH] removed bug where agent would see its own prediction as
conflict
---
examples/training_example.py | 2 +-
flatland/envs/observations.py | 24 +++++++++++++++---------
2 files changed, 16 insertions(+), 10 deletions(-)
diff --git a/examples/training_example.py b/examples/training_example.py
index ad8396a..218f133 100644
--- a/examples/training_example.py
+++ b/examples/training_example.py
@@ -16,7 +16,7 @@ env = RailEnv(width=20,
height=20,
rail_generator=complex_rail_generator(nr_start_goal=10, nr_extra=1, min_dist=8, max_dist=99999, seed=0),
obs_builder_object=TreeObservation,
- number_of_agents=1)
+ number_of_agents=2)
# Import your own Agent or use RLlib to train agents on Flatland
diff --git a/flatland/envs/observations.py b/flatland/envs/observations.py
index b492502..931fabc 100644
--- a/flatland/envs/observations.py
+++ b/flatland/envs/observations.py
@@ -334,18 +334,24 @@ class TreeObsForRailEnv(ObservationBuilder):
int_position = coordinate_to_position(self.env.width, [position])
pre_step = max(0, num_steps - 1)
post_step = min(self.max_prediction_depth - 1, num_steps + 1)
+ # Look for opposing paths at distance num_step
if int_position in np.delete(self.predicted_pos[num_steps], handle):
- conflicting_agent = np.where(np.delete(self.predicted_pos[num_steps], handle) == int_position)[0][0]
- if direction != self.predicted_dir[num_steps][conflicting_agent]:
- potential_conflict = 1
+ conflicting_agent = np.where(np.delete(self.predicted_pos[num_steps], handle) == int_position)
+ for ca in conflicting_agent:
+ if direction != self.predicted_dir[num_steps][ca[0]]:
+ potential_conflict = 1
+ # Look for opposing paths at distance num_step-1
elif int_position in np.delete(self.predicted_pos[pre_step], handle):
- conflicting_agent = np.where(np.delete(self.predicted_pos[pre_step], handle) == int_position)[0][0]
- if direction != self.predicted_dir[pre_step][conflicting_agent]:
- potential_conflict = 1
+ conflicting_agent = np.where(self.predicted_pos[pre_step] == int_position)
+ for ca in conflicting_agent:
+ if direction != self.predicted_dir[pre_step][ca[0]]:
+ potential_conflict = 1
+ # Look for opposing paths at distance num_step+1
elif int_position in np.delete(self.predicted_pos[post_step], handle):
- conflicting_agent = np.where(np.delete(self.predicted_pos[post_step], handle) == int_position)[0][0]
- if direction != self.predicted_dir[post_step][conflicting_agent]:
- potential_conflict = 1
+ conflicting_agent = np.where(np.delete(self.predicted_pos[post_step], handle) == int_position)
+ for ca in conflicting_agent:
+ if direction != self.predicted_dir[post_step][ca[0]]:
+ potential_conflict = 1
if position in self.location_has_target and position != agent.target:
if num_steps < other_target_encountered:
--
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