diff --git a/src/extra.py b/src/extra.py
index 48a3249377f6ef3ac8b5f6f0d3c756c3130f1ed4..4da16330b8b2e354f62b3234c4dbcca33958ecef 100644
--- a/src/extra.py
+++ b/src/extra.py
@@ -1,13 +1,36 @@
+#
+# Author Adrian Egli
+#
+# This observation solves the FLATland challenge ROUND 1 - with agent's done 19.3%
+#
+# Training:
+# For the training of the PPO RL agent I showed 10k episodes - The episodes used for the training
+# consists of 1..20 agents on a 50x50 grid. Thus the RL agent has to learn to handle 1 upto 20 agents.
+#
+# - https://github.com/mitchellgoffpc/flatland-training
+#
+# The key idea behind this observation is that agent's can not freely choose where they want.
+#
+# ./images/adrian_egli_decisions.png
+# ./images/adrian_egli_info.png
+# ./images/adrian_egli_start.png
+# ./images/adrian_egli_target.png
+#
+# Private submission
+# http://gitlab.aicrowd.com/adrian_egli/neurips2020-flatland-starter-kit/issues/8
+
import numpy as np
from flatland.core.env_observation_builder import ObservationBuilder
from flatland.core.grid.grid4_utils import get_new_position
from flatland.envs.agent_utils import RailAgentStatus
-# Adrian Egli performance fix (the fast methods brings more than 50%)
from flatland.envs.rail_env import RailEnvActions
from src.ppo.agent import Agent
+# ------------------------------------- USE FAST_METHOD from FLATland master ------------------------------------------
+# Adrian Egli performance fix (the fast methods brings more than 50%)
+
def fast_isclose(a, b, rtol):
return (a < (b + rtol)) or (a < (b - rtol))
@@ -37,6 +60,8 @@ def fast_count_nonzero(possible_transitions: (int, int, int, int)):
return possible_transitions[0] + possible_transitions[1] + possible_transitions[2] + possible_transitions[3]
+# ------------------------------- END - USE FAST_METHOD from FLATland master ------------------------------------------
+
class Extra(ObservationBuilder):
def __init__(self, max_depth):
@@ -171,90 +196,6 @@ class Extra(ObservationBuilder):
def normalize_observation(self, obsData):
return obsData
- def check_deadlock(self, only_next_cell_check=True, handle=None):
- agents_with_deadlock = []
- agents = range(self.env.get_num_agents())
- if handle is not None:
- agents = [handle]
- for a in agents:
- if self.env.agents[a].status < RailAgentStatus.DONE:
- position = self.env.agents[a].position
- first_step = True
- if position is None:
- position = self.env.agents[a].initial_position
- first_step = True
- direction = self.env.agents[a].direction
- while position is not None: # and position != self.env.agents[a].target:
- possible_transitions = self.env.rail.get_transitions(*position, direction)
- # num_transitions = np.count_nonzero(possible_transitions)
- agents_on_switch, agents_near_to_switch, agents_near_to_switch_all = self.check_agent_descision(
- position,
- direction,
- self.switches,
- self.switches_neighbours)
-
- if not agents_on_switch or first_step:
- first_step = False
- new_direction_me = np.argmax(possible_transitions)
- new_cell_me = get_new_position(position, new_direction_me)
- opp_agent = self.env.agent_positions[new_cell_me]
- if opp_agent != -1:
- opp_position = self.env.agents[opp_agent].position
- opp_direction = self.env.agents[opp_agent].direction
- opp_agents_on_switch, opp_agents_near_to_switch, agents_near_to_switch_all = \
- self.check_agent_descision(opp_position,
- opp_direction,
- self.switches,
- self.switches_neighbours)
-
- # opp_possible_transitions = self.env.rail.get_transitions(*opp_position, opp_direction)
- # opp_num_transitions = np.count_nonzero(opp_possible_transitions)
- if not opp_agents_on_switch:
- if opp_direction != direction:
- agents_with_deadlock.append(a)
- position = None
- else:
- if only_next_cell_check:
- position = None
- else:
- position = new_cell_me
- direction = new_direction_me
- else:
- if only_next_cell_check:
- position = None
- else:
- position = new_cell_me
- direction = new_direction_me
- else:
- if only_next_cell_check:
- position = None
- else:
- position = new_cell_me
- direction = new_direction_me
- else:
- position = None
-
- return agents_with_deadlock
-
- def is_collision(self, obsData):
- if obsData[4] == 1:
- # Agent is READY_TO_DEPART
- return False
- if obsData[6] == 1:
- # Agent is DONE / DONE_REMOVED
- return False
-
- same_dir = obsData[18] + obsData[19] + obsData[20] + obsData[21]
- if same_dir > 0:
- # Agent detect an agent walking in same direction and between the agent and the other agent there are all
- # cell unoccupied. (Follows the agents)
- return False
- freedom = obsData[10] + obsData[11] + obsData[12] + obsData[13]
- blocked = obsData[14] + obsData[15] + obsData[16] + obsData[17]
- # if the Agent has equal freedom or less then the agent can not avoid the agent travelling towards
- # (opposite) direction -> this can cause a deadlock (locally tested)
- return freedom <= blocked and freedom > 0
-
def reset(self):
self.build_data()
return
diff --git a/src/images/adrian_egli_decisions.png b/src/images/adrian_egli_decisions.png
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diff --git a/src/images/adrian_egli_start.png b/src/images/adrian_egli_start.png
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diff --git a/src/images/adrian_egli_target.png b/src/images/adrian_egli_target.png
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