def utility(self, data):
# every 1500 is 0.1
enemy_dist = data.enemy.location.dist(data.ball.location)
enemy_dist_u = enemy_dist * 0.00006
dist01 = rlu.dist_01(data.car.dist_to_ball)
dist01 = 1 - easing.smooth_stop(4, dist01)
car_to_ball = data.ball.location - data.car.location
above_ang = car_to_ball.ang_to(Vec3(z=1))
aa01 = easing.fix(1 - 1.5 * above_ang / math.pi)
return easing.fix(0.76 * aa01 + enemy_dist_u) * (data.ball.location.z > 25)
def utility(self, data):
ball_soon = predict.move_ball(data.ball.copy(), 1)
team_sign = datalibs.team_sign(data.car.team)
own_half_01 = easing.fix(easing.remap(team_sign * datalibs.ARENA_LENGTH2, (-1 * team_sign) * datalibs.ARENA_LENGTH2, 0.0, 1.1, ball_soon.location.y))
self.ball_to_goal_right = self.enemy_goal_right - data.ball_when_hit.location
self.ball_to_goal_left = self.enemy_goal_left - data.ball_when_hit.location
self.aim_cone = route.AimCone(self.ball_to_goal_right.ang(), self.ball_to_goal_left.ang())
car_to_ball = data.ball_when_hit.location - data.car.location
in_position = self.aim_cone.contains_direction(car_to_ball)
return easing.fix(own_half_01 + 0.06 * in_position)
def utility(self, data):
car_to_pad = self.location - data.car.location_2d
state = data.packet.game_boosts[self.index]
if not state.is_active:
return 0
# consider distance, angle, and size
dist = 1 - rlu.dist_01(data.car.location.dist(self.location))
ang = rlu.face_ang_01(data.car.orientation.front.ang_to_flat(car_to_pad))
big = 1 if self.info.is_full_boost else 0.65
# prefer those closer to own goal
between_car_and_goal = datalibs.is_point_closer_to_goal(self.location, data.car.location, data.car.team)
btcg = 1 if between_car_and_goal else 0.9
off_dist_01 = 1
if data.agent.point_of_interest is not None and False:
# Only deviate if pot is far away and there is time to collect boost
car_to_pot_dist = data.car.location.dist(data.agent.point_of_interest)
pad_to_car_dist = data.car.location.dist(self.location)
pad_to_pot_dist = data.agent.point_of_interest.dist(self.location)
if car_to_pot_dist > 1200 and pad_to_car_dist < pad_to_pot_dist:
# prefer those between car and point of interest
off_dist_01 = rlu.dist_01(pad_to_car_dist + pad_to_pot_dist - car_to_pot_dist)
off_dist_01 = 1 - off_dist_01**2
else:
off_dist_01 = 0
result = easing.fix(dist * ang * big * btcg * off_dist_01)
# data.renderer.draw_line_3d(data.car.location.tuple(), self.location.tuple(), data.renderer.create_color(255, 0, int(result * 255), 0))
return result
def utility(self, data):
team_sign = datalibs.team_sign(data.car.team)
ball_to_goal = datalibs.get_goal_location(data.car.team) - data.ball.location
ball_vel_g = data.ball.velocity.proj_onto_size(ball_to_goal)
if ball_vel_g > 0:
vel_g_01 = easing.fix(ball_vel_g / 700 + 0.36)
else:
vel_g_01 = 0
too_close = ball_to_goal.length2() < 900*900
hits_goal_prediction = predict.will_ball_hit_goal(data.ball)
hits_goal = hits_goal_prediction.happens and rlmath.sign(data.ball.velocity.y) == team_sign and hits_goal_prediction.time < 6
return easing.fix(vel_g_01) or hits_goal or too_close
def utility(self, data):
team_sign = datalibs.team_sign(data.car.team)
ball_to_goal = datalibs.get_goal_location(data.car.team) - data.ball.location
ball_vel_g = data.ball.velocity.proj_onto_size(ball_to_goal)
if ball_vel_g > 0:
vel_g_01 = easing.fix(ball_vel_g / 1000 + 0.5)
else:
vel_g_01 = easing.fix(0.5 + ball_vel_g / 3000)
ball_on_my_half_01 = easing.fix(easing.remap((-1*team_sign) * datalibs.ARENA_LENGTH2, team_sign * datalibs.ARENA_LENGTH2, 0, 1.6, data.ball.location.y))
enemy_on_my_half_01 = easing.fix(easing.remap((-1*team_sign) * datalibs.ARENA_LENGTH2, team_sign * datalibs.ARENA_LENGTH2, 0.5, 1.1, data.ball.location.y))
enemy_reaches_first = predict.time_till_reach_ball(data.ball, data.enemy) < data.time_till_hit
enemy_first_01 = 1 if enemy_reaches_first else 0.6
return easing.fix(ball_on_my_half_01 * enemy_on_my_half_01 * vel_g_01 * enemy_first_01)
def utility(self, data):
team_sign = datalibs.team_sign(data.car.team)
goal_to_ball = data.ball.location - datalibs.get_goal_location(data.car.team)
car_to_ball = data.ball.location - data.car.location
ball_own_half_01 = easing.fix(easing.remap((-1*team_sign) * datalibs.ARENA_LENGTH2, team_sign * datalibs.ARENA_LENGTH2, -0.2, 1.2, data.ball.location.y))
car_to_ball = data.ball_when_hit.location - data.car.location
in_position = self.aim_cone.contains_direction(car_to_ball)
return ball_own_half_01 * in_position
def utility(self, data):
if data.car.boost == 100:
return -0.5
boost01 = data.car.boost / 100.0
boost01 = 1 - easing.smooth_stop(4, boost01)
# best_boost = self.collect_boost_system.evaluate(data)
pot_01 = 1
if data.agent.point_of_interest is not None:
# Agent have a point of interest. Only collect boost if missing speed and boost
pot_01 = easing.fix(1 - data.car.velocity.length() / 2500) # 2500 so he is always missing some speed
ut = boost01 * pot_01
return easing.inv_lerp(0, 0.9, ut)
def dist_01(dist, max_dist=MAX_DIST): return easing.fix(dist / float(max_dist))
def face_ang_01(ang): return easing.fix(math.cos(ang))