Commit 5bf451eb authored by spiglerg's avatar spiglerg
Browse files

prevent stopping in the middle of a cell

parent 65397f68
......@@ -28,19 +28,32 @@ class EnvAgentStatic(object):
position = attrib()
direction = attrib()
target = attrib()
moving = attrib()
def __init__(self, position, direction, target, moving=False):
moving = attrib(default=False)
# speed_data: speed is added to position_fraction on each moving step, until position_fraction>=1.0,
# after which 'transition_action_on_cellexit' is executed (equivalent to executing that action in the previous
# cell if speed=1, as default)
speed_data = attrib(default=dict({'position_fraction': 0.0, 'speed': 1.0, 'transition_action_on_cellexit': 0}))
def __init__(self,
position,
direction,
target,
moving=False,
speed_data={'position_fraction': 0.0, 'speed': 1.0, 'transition_action_on_cellexit': 0}):
self.position = position
self.direction = direction
self.target = target
self.moving = moving
self.speed_data = speed_data
@classmethod
def from_lists(cls, positions, directions, targets):
""" Create a list of EnvAgentStatics from lists of positions, directions and targets
"""
return list(starmap(EnvAgentStatic, zip(positions, directions, targets, [False] * len(positions))))
speed_datas = []
for i in range(len(positions)):
speed_datas.append({'position_fraction': 0.0, 'speed': 1.0, 'transition_action_on_cellexit': 0})
return list(starmap(EnvAgentStatic, zip(positions, directions, targets, [False] * len(positions), speed_datas)))
def to_list(self):
......@@ -54,7 +67,7 @@ class EnvAgentStatic(object):
if type(lTarget) is np.ndarray:
lTarget = lTarget.tolist()
return [lPos, int(self.direction), lTarget, int(self.moving)]
return [lPos, int(self.direction), lTarget, int(self.moving), self.speed_data]
@attrs
......@@ -78,7 +91,7 @@ class EnvAgent(EnvAgentStatic):
def to_list(self):
return [
self.position, self.direction, self.target, self.handle,
self.old_direction, self.old_position, self.moving]
self.old_direction, self.old_position, self.moving, self.speed_data]
@classmethod
def from_static(cls, oStatic):
......
......@@ -73,7 +73,7 @@ class RailEnv(Environment):
random_rail_generator : generate a random rail of given size
rail_from_GridTransitionMap_generator(rail_map) : generate a rail from
a GridTransitionMap object
rail_from_manual_specifications_generator(rail_spec) : generate a rail from
rail_from_manual_sp ecifications_generator(rail_spec) : generate a rail from
a rail specifications array
TODO: generate_rail_from_saved_list or from list of ndarray bitmaps ---
width : int
......@@ -101,7 +101,6 @@ class RailEnv(Environment):
self.action_space = [1]
self.observation_space = self.obs_builder.observation_space # updated on resets?
self.actions = [0] * number_of_agents
self.rewards = [0] * number_of_agents
self.done = False
......@@ -192,29 +191,33 @@ class RailEnv(Environment):
# for i in range(len(self.agents_handles)):
for iAgent in range(self.get_num_agents()):
agent = self.agents[iAgent]
if iAgent not in action_dict: # no action has been supplied for this agent
if agent.moving:
# Keep moving
# Change MOVE_FORWARD to DO_NOTHING
action_dict[iAgent] = RailEnvActions.DO_NOTHING
else:
action_dict[iAgent] = RailEnvActions.DO_NOTHING
agent.speed_data['speed']=0.5
if self.dones[iAgent]: # this agent has already completed...
continue
action = action_dict[iAgent]
if action < 0 or action > len(RailEnvActions):
print('ERROR: illegal action=', action,
'for agent with index=', iAgent)
return
if np.equal(agent.position, agent.target).all():
self.dones[iAgent] = True
else:
self.rewards_dict[iAgent] += step_penalty * agent.speed_data['speed']
if iAgent not in action_dict: # no action has been supplied for this agent
action_dict[iAgent] = RailEnvActions.DO_NOTHING
if action_dict[iAgent] < 0 or action_dict[iAgent] > len(RailEnvActions):
print('ERROR: illegal action=', action_dict[iAgent],
'for agent with index=', iAgent,
'"DO NOTHING" will be executed instead')
action_dict[iAgent] = RailEnvActions.DO_NOTHING
action = action_dict[iAgent]
if action == RailEnvActions.DO_NOTHING and agent.moving:
# Keep moving
action = RailEnvActions.MOVE_FORWARD
if action == RailEnvActions.STOP_MOVING and agent.moving:
if action == RailEnvActions.STOP_MOVING and agent.moving and agent.speed_data['position_fraction'] < 0.01:
# Only allow halting an agent on entering new cells.
agent.moving = False
self.rewards_dict[iAgent] += stop_penalty
......@@ -223,47 +226,73 @@ class RailEnv(Environment):
agent.moving = True
self.rewards_dict[iAgent] += start_penalty
if action != RailEnvActions.DO_NOTHING and action != RailEnvActions.STOP_MOVING:
cell_isFree, new_cell_isValid, new_direction, new_position, transition_isValid = \
self._check_action_on_agent(action, agent)
if all([new_cell_isValid, transition_isValid, cell_isFree]):
agent.old_direction = agent.direction
agent.old_position = agent.position
agent.position = new_position
agent.direction = new_direction
else:
# Logic: if the chosen action is invalid,
# and it was LEFT or RIGHT, and the agent was moving, then keep moving FORWARD.
if (action == RailEnvActions.MOVE_LEFT or action == RailEnvActions.MOVE_RIGHT) and agent.moving:
cell_isFree, new_cell_isValid, new_direction, new_position, transition_isValid = \
self._check_action_on_agent(RailEnvActions.MOVE_FORWARD, agent)
if all([new_cell_isValid, transition_isValid, cell_isFree]):
agent.old_direction = agent.direction
agent.old_position = agent.position
agent.position = new_position
agent.direction = new_direction
# Now perform a movement.
# If the agent is in an initial position within a new cell (agent.speed_data['position_fraction']<eps)
# store the desired action in `transition_action_on_cellexit' (only if the desired transition is
# allowed! otherwise DO_NOTHING!)
# Then in any case (if agent.moving) and the `transition_action_on_cellexit' is valid, increment the
# position_fraction by the speed of the agent (regardless of action taken, as long as no
# STOP_MOVING, but that makes agent.moving=False)
# If the new position fraction is >= 1, reset to 0, and perform the stored
# transition_action_on_cellexit
# If the agent can make an action
action_selected = False
if agent.speed_data['position_fraction'] < 0.01:
if action != RailEnvActions.DO_NOTHING and action != RailEnvActions.STOP_MOVING:
cell_isFree, new_cell_isValid, new_direction, new_position, transition_isValid = \
self._check_action_on_agent(action, agent)
if all([new_cell_isValid, transition_isValid, cell_isFree]):
agent.speed_data['transition_action_on_cellexit'] = action
action_selected = True
else:
# But, if the chosen invalid action was LEFT/RIGHT, and the agent is moving,
# try to keep moving forward!
if (action == RailEnvActions.MOVE_LEFT or action == RailEnvActions.MOVE_RIGHT) and agent.moving:
cell_isFree, new_cell_isValid, new_direction, new_position, transition_isValid = \
self._check_action_on_agent(RailEnvActions.MOVE_FORWARD, agent)
if all([new_cell_isValid, transition_isValid, cell_isFree]):
agent.speed_data['transition_action_on_cellexit'] = RailEnvActions.MOVE_FORWARD
action_selected = True
else:
# TODO: an invalid action was chosen after entering the cell. The agent cannot move.
self.rewards_dict[iAgent] += invalid_action_penalty
agent.moving = False
self.rewards_dict[iAgent] += stop_penalty
continue
else:
# the action was not valid, add penalty
# TODO: an invalid action was chosen after entering the cell. The agent cannot move.
self.rewards_dict[iAgent] += invalid_action_penalty
agent.moving = False
self.rewards_dict[iAgent] += stop_penalty
continue
else:
# the action was not valid, add penalty
self.rewards_dict[iAgent] += invalid_action_penalty
if agent.moving and (action_selected or agent.speed_data['position_fraction'] >= 0.01):
agent.speed_data['position_fraction'] += agent.speed_data['speed']
if np.equal(agent.position, agent.target).all():
self.dones[iAgent] = True
else:
self.rewards_dict[iAgent] += step_penalty
if agent.speed_data['position_fraction'] >= 1.0:
agent.speed_data['position_fraction'] = 0.0
# Perform stored action to transition to the next cell
# Now 'transition_action_on_cellexit' will be guaranteed to be valid; it was checked on entering
# the cell
cell_isFree, new_cell_isValid, new_direction, new_position, transition_isValid = \
self._check_action_on_agent(agent.speed_data['transition_action_on_cellexit'], agent)
agent.old_direction = agent.direction
agent.old_position = agent.position
agent.position = new_position
agent.direction = new_direction
# Check for end of episode + add global reward to all rewards!
if np.all([np.array_equal(agent2.position, agent2.target) for agent2 in self.agents]):
self.dones["__all__"] = True
self.rewards_dict = [0 * r + global_reward for r in self.rewards_dict]
# Reset the step actions (in case some agent doesn't 'register_action'
# on the next step)
self.actions = [0] * self.get_num_agents()
return self._get_observations(), self.rewards_dict, self.dones, {}
def _check_action_on_agent(self, action, agent):
......@@ -271,6 +300,7 @@ class RailEnv(Environment):
# cell used to check for invalid actions
new_direction, transition_isValid = self.check_action(agent, action)
new_position = get_new_position(agent.position, new_direction)
# Is it a legal move?
# 1) transition allows the new_direction in the cell,
# 2) the new cell is not empty (case 0),
......@@ -281,11 +311,13 @@ class RailEnv(Environment):
np.clip(new_position, [0, 0], [self.height - 1, self.width - 1]))
and # check the new position has some transitions (ie is not an empty cell)
self.rail.get_transitions(new_position) > 0)
# If transition validity hasn't been checked yet.
if transition_isValid is None:
transition_isValid = self.rail.get_transition(
(*agent.position, agent.direction),
new_direction)
# Check the new position is not the same as any of the existing agent positions
# (including itself, for simplicity, since it is moving)
cell_isFree = not np.any(
......
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