def process_move_from_state(self):
new_puck_pos = utils.next_pos_from_state(self.state)
# after initial position check for idleness
if self.in_initial_state is not None:
# if puck position changed, OK
if new_puck_pos['x'] != self.state['puck_pos']['x']:
self.in_initial_state = None
# if number of idle moves exceeded, penalize with goal
elif self.in_initial_state >= self.max_idle_moves:
goal_for = 'left' if self.state['puck_pos']['x'] > self.board.shape[1]/2 else 'right'
self.process_goal_for(goal_for, puck_to=('left' if goal_for == 'left' else 'right'))
return goal_for
# if idle but idle moves not exceed, increment counter
else:
self.in_initial_state += 1
# update pos in state
self.state['puck_pos'] = new_puck_pos
# if is goal
if utils.is_goal(self.state) is not None:
self.process_goal_for(utils.is_goal(self.state))
return utils.is_goal(self.state)
# update speed (and direction) in state
self.state['puck_speed'] = utils.next_speed(self.state)
return None
def doorkey_problem(env, info):
'''
You are required to find the optimal path in
doorkey-5x5-normal.env
doorkey-6x6-normal.env
doorkey-8x8-normal.env
doorkey-6x6-direct.env
doorkey-8x8-direct.env
doorkey-6x6-shortcut.env
doorkey-8x8-shortcut.env
Feel Free to modify this fuction
'''
state_space, state_to_idx = generate_state_space(env, info)
control_space = [MF, TL, TR, PK, UD]
V, pi = dp.DP(state_space, state_to_idx, control_space, dp.get_next_state,
dp.step_cost, dp.terminal_cost, env)
# get optimal sequence
state = utils.get_initial_state(info)
optim_act_seq = []
t = 0
while not utils.is_goal(state, info["goal_pos"]):
state_idx = state_to_idx[utils.hash_state(state)]
optimal_control = pi[t, state_idx]
optim_act_seq.append(optimal_control)
# get next state
state = dp.get_next_state(state, optimal_control, env)
t += 1
return optim_act_seq
def estimate_path(current_state, after_time):
state = copy.copy(current_state)
path = []
while after_time > 0:
state['puck_pos'] = utils.next_pos_from_state(state)
if utils.is_goal(state) is not None:
break
if utils.next_after_boundaries(state):
state['puck_speed'] = utils.next_after_boundaries(state)
path.append((state['puck_pos'], state['puck_speed']))
after_time -= state['delta_t']
return path
def estimate_path(current_state, after_time):
""" Function that function estimates the next moves in a after_time window
Returns:
list: coordinates and speed of puck for next ticks
"""
state = copy.copy(current_state)
path = []
while after_time > 0:
state['puck_pos'] = utils.next_pos_from_state(state)
if utils.is_goal(state) is not None:
break
if utils.next_after_boundaries(state):
state['puck_speed'] = utils.next_after_boundaries(state)
path.append((state['puck_pos'], state['puck_speed']))
after_time -= state['delta_t']
return path
