def _optimal_striker_pos(state: PlayerState) -> Coordinate:
side = 1 if state.world_view.side == 'l' else -1
if not state.world_view.ball.is_value_known():
return state.get_global_play_pos()
ball: Coordinate = state.world_view.ball.get_value().coord
play_position = state.get_global_play_pos()
ball_delta_y = ball.pos_y - play_position.pos_y
if side * ball.pos_x > 0:
# Attacking
x_offset = ball.pos_x + side * 5
optimal_x = clamp(play_position.pos_x + x_offset, -45, 45)
# Used to make players position themselves closer to the goal on the y-axis when far up/down the field
y_goal_factor = 0.982888 + 0.002871167 * abs(
optimal_x) - 0.0000807057 * pow(optimal_x, 2)
optimal_y = clamp(
play_position.pos_y + ball.pos_y * 0.2 + ball_delta_y * 0.4, -30,
30) * y_goal_factor
if state.world_view.team_has_ball(state.team_name, max_data_age=4):
opt_coord = Coordinate(optimal_x + (10 * side), optimal_y)
free_pos = state.get_closest_free_position(opt_coord)
if state.is_test_player():
debug_msg("Free position:{0}".format(free_pos),
"FREE_POSITION")
return opt_coord if free_pos is None else free_pos
return Coordinate(optimal_x, optimal_y)
else:
# Defending
optimal_x = -state.get_global_play_pos().pos_x + ball.pos_x * 0.4
optimal_y = state.get_global_play_pos().pos_y + ball_delta_y * 0.2
if state.world_view.team_has_ball(state.team_name, max_data_age=4):
opt_coord = Coordinate(optimal_x + (10 * side), optimal_y)
free_pos = state.get_closest_free_position(opt_coord)
if state.is_test_player():
debug_msg("Free position:{0}".format(free_pos),
"FREE_POSITION")
return opt_coord if free_pos is None else free_pos
return Coordinate(optimal_x, optimal_y)
def determine_objective_field_default(state: PlayerState):
state.intercepting = False
# If lost orientation -> blind orient
if _lost_orientation(state):
return Objective(state, lambda: actions.blind_orient(state),
lambda: True, 1)
opponent_side = "r" if state.world_view.side == "l" else "l"
# If game not started or other team starting -> Idle orientation
if state.world_view.game_state == 'before_kick_off' or state.world_view.game_state == "kick_off_{0}".format(
opponent_side) or "goal" in state.world_view.game_state:
return Objective(state, lambda: actions.idle_orientation(state),
lambda: True, 1)
# If some fault has been made by our team -> position optimally
if "fault_{0}".format(
state.world_view.side) in state.world_view.game_state:
return _position_optimally_objective(state)
# If we have a free kick, corner_kick, kick_in or kick_off
# If closest -> Go to ball and pass, else position optimally
if state.world_view.game_state == "free_kick_{0}".format(state.world_view.side) \
or state.world_view.game_state == "corner_kick_{0}".format(state.world_view.side) \
or state.world_view.game_state == "kick_in_{0}".format(state.world_view.side) \
or state.world_view.game_state == "kick_off_{0}".format(state.world_view.side) \
or state.world_view.game_state == "offside_{0}".format(opponent_side):
if _ball_unknown(state):
return _locate_ball_objective(state)
if state.is_near_ball(KICKABLE_MARGIN):
if state.world_view.sim_time - state.action_history.last_look_for_pass_targets > 2:
return Objective(state,
lambda: actions.look_for_pass_target(state),
lambda: True, 2)
if _choose_pass_target(state, must_pass=True) is not None:
return Objective(
state, lambda: actions.pass_to_player(
state, _choose_pass_target(state, must_pass=True)),
lambda: True, 1)
else:
return Objective(state,
lambda: actions.look_for_pass_target(state),
lambda: True, 2)
elif state.is_nearest_ball(1):
return _jog_to_ball_objective(state)
else:
return _position_optimally_objective(state)
# If in dribbling mode -> Dribble
if state.mode is DRIBBLING_MODE:
return _dribble_objective(state)
# If in possession mode -> Pass
if state.mode is POSSESSION_MODE:
return _pass_objective(state)
# If position known, but ball not -> Locate ball
if _ball_unknown(state):
return _locate_ball_objective(state)
# If in possession of ball -> dribble!
if state.is_near_ball() and state.is_nearest_ball(1):
state.mode = DRIBBLING_MODE
return _dribble_objective(state)
required_degree = calculate_required_degree(state)
if state.is_nearest_ball(required_degree):
intercept_actions = actions.intercept_2(state)
state.intercepting = True
if intercept_actions is not None:
return Objective(state, lambda: intercept_actions)
else:
return _rush_to_ball_objective(state)
# If ball not incoming -> Position optimally while looking at ball
if not state.ball_incoming() and not configurations.USING_PASS_CHAIN_STRAT:
if state.is_test_player():
debug_msg(str(state.now()) + " Position optimally!", "ACTIONS")
return _position_optimally_objective(state)
if state.is_test_player():
debug_msg(str(state.now()) + " Idle orientation!", "ACTIONS")
return Objective(state, lambda: actions.idle_orientation(state),
lambda: True, 1)
def _update_dribble_or_pass_model(state: PlayerState, model: UppaalModel):
# This function edits the UPPAAL file to represent the current state of the game
# Amount of ticks to forecast game state
# This should be the expected time that it takes to generate the strategy
FORECAST_TICKS = 6
team_mates = state.world_view.get_teammates_precarious(state.team_name,
10,
min_dist=5)
opponents = state.world_view.get_opponents_precarious(state.team_name,
10,
min_dist=0)
# Forecast position of the ball possessor
if state.get_y_north_velocity_vector() is not None:
possessor_forecasted = (
state.position.get_value().vector() +
state.get_y_north_velocity_vector() * FORECAST_TICKS).coord()
else:
possessor_forecasted = state.position.get_value()
# Forecast position of other players
forecasted_team_positions = list(
map(
lambda p: p.get_value().forecasted_position(
(state.now() - p.last_updated_time) + FORECAST_TICKS),
team_mates))
forecasted_opponent_positions = list(
map(
lambda p: p.get_value().forecasted_position(
(state.now() - p.last_updated_time) + FORECAST_TICKS),
opponents))
if state.players_close_behind > 0:
forecasted_opponent_positions.append(
Coordinate(
possessor_forecasted.pos_x - 1,
possessor_forecasted.pos_y,
))
# Convert to textual format understandable by uppaal
team_pos_value = _to_3d_double_array_coordinate(forecasted_team_positions)
opponent_pos_value = _to_3d_double_array_coordinate(
forecasted_opponent_positions)
possessor_val = _to_2d_double_array_coordinate(possessor_forecasted)
model.set_global_declaration_value("TEAM_MATES",
len(forecasted_team_positions))
model.set_global_declaration_value("OPPONENTS",
len(forecasted_opponent_positions))
model.set_global_declaration_value("team_pos[TEAM_MATES][2]",
team_pos_value)
model.set_global_declaration_value("opponent_pos[OPPONENTS][2]",
opponent_pos_value)
model.set_global_declaration_value("possessor[2]", possessor_val)
if state.is_test_player(): # Debugging
all_posis = list(
map(lambda p: p.get_value().coord, state.world_view.other_players))
debug_msg(
str(state.now()) + " All positions: " + str(all_posis),
"DRIBBLE_PASS_MODEL")
debug_msg(
str(state.now()) + " Forecasted team positions: " +
str(team_pos_value), "DRIBBLE_PASS_MODEL")
debug_msg(
str(state.now()) + " Forecasted opponent positions: " +
str(opponent_pos_value), "DRIBBLE_PASS_MODEL")
debug_msg(
str(state.now()) + " Forecasted possessor position: " +
str(possessor_val), "DRIBBLE_PASS_MODEL")
return forecasted_team_positions
