""" Python translation of artificialIntelligence.js Assumes the existence of Python equivalents of the original JS modules: game_logic (equivalent of ./public/js/gameLogic.js) misc (equivalent of ./public/js/misc.js) with the same public interface used below: misc.reduce_precision(value, digits) -> rdz misc.Vector(origin, direction) misc.k2b(down_keys_dict) -> bitmask encoding of key dict misc.b2k(bitmask) -> key dict decoding of bitmask game_logic.MsgTypes game_logic.UpgradeTypes game_logic.GameStates game_logic.player_count (module-level "playerCount") Player objects are expected to expose the same attributes/methods as in the JS version (pos, targetPosition -> target_position, dir, reach, health, evaluation, evaluate_dist(), dist(), etc.) The public attribute names have been converted to snake_case; adjust to match your actual Player implementation if it uses different naming. """ import time import json import random import math import game_logic as gl import misc rdz = misc.reduce_precision MsgTypes = gl.MsgTypes Vector = misc.Vector UpgradeTypes = gl.UpgradeTypes def down_keys_from_direction(dx, dy): down_keys = {'a': False, 's': False, 'd': False, 'w': False, ' ': False} dmax = max(abs(dx), abs(dy)) dx = dx / dmax dy = dy / dmax if dx > 0.6: down_keys['d'] = True if dx < -0.6: down_keys['a'] = True if dy > 0.6: down_keys['w'] = True if dy < -0.6: down_keys['s'] = True return down_keys class ManagerAI: def __init__(self, tournament_handler, team_tournament_state): self.tournament_handler = tournament_handler self.team_id = team_tournament_state.id self.team_tournament_state = team_tournament_state self.name = "Steel Fury" self.is_ai = True def on_message(self, data, ws): pass def manage_team(self): print("ai manageTeam") msg = { 't': MsgTypes.PlayerUpgrade, 'pi': gl.player_count, 'ut': UpgradeTypes.SpeedUpgrade, } self.on_message(json.dumps(msg), self) msg = { 't': MsgTypes.TeamManagementDone, } self.on_message(json.dumps(msg), self) class TeamAI: def __init__(self, game_logic_instance, team, arena): self.current_time_stamp = int(time.time() * 1000) self.team = team self.game_logic = game_logic_instance self.arena = arena self.pre_game_ready = False self.players_ready = False self.ai_only = False self.correction_needed_threshold = 1 def _reaction_time(self, player): """ Compute how long (ms) this player takes to react before making a new decision. Less intelligent players are slower on average, but every player also gets some human-like variability: - gaussian jitter around their base reaction time - a small chance of a "lapse" (a noticeably slower reaction), simulating a momentary loss of focus """ base = (100 - player.intelligence) * (8 + random.random() * 8) # +/- ~20% gaussian jitter around the base reaction time jitter = random.gauss(0, base * 0.2) reaction_time = base + jitter # occasional lapse in concentration: rare, but noticeably slower if random.random() < 0.04: reaction_time *= random.uniform(1.5, 3.0) return max(0, reaction_time) def update(self): self.current_time_stamp = int(time.time() * 1000) team_no = 1 if self.game_logic.team1 is self.team else 2 direction = -1 if (self.game_logic.round % 2) == 1 else 1 if team_no == 2: direction *= -1 if self.game_logic.state != gl.GameStates.Playing: if self.game_logic.state == gl.GameStates.PreGame: pre_game_ready = True for i, player in enumerate(self.team): sep_dist = 100 player.target_position.x = (i * sep_dist) % (sep_dist * 4) - 1.5 * sep_dist player.target_position.y = direction * (math.floor(i / 4) * sep_dist + 75) if player.dist(player.target_position) > player.reach and player.health > 50: pre_game_ready = False self.pre_game_ready = pre_game_ready elif self.game_logic.state in (gl.GameStates.GetReady, gl.GameStates.Goal): ready = True for player in self.team: player.controlled = False player.target_position.x = player.default_position.x player.target_position.y = player.default_position.y if player.dist(player.target_position) > player.reach and player.health > 50: ready = False if len(player.collisions) > 0: dx = player.target_position.x - player.pos.x dy = player.target_position.y - player.pos.y alpha = math.atan2(dy, dx) + math.pi / 4 dist = math.sqrt(dx * dx + dy * dy) player.target_position.x = player.pos.x + math.cos(alpha) * dist player.target_position.y = player.pos.y + math.sin(alpha) * dist self.players_ready = ready else: # ----- PLAYING ----- if self.game_logic.ball_handler is not None: if self.game_logic.ball_handler in self.team: # this team has the ball for player in self.team: if player is self.game_logic.ball_handler: if not self.ai_only: player.controlled = True if player.dist(player.default_position) > player.max_travel_dist: player.evaluation.close = True player.target_position.x = 0 player.target_position.y = -direction * 835 if abs(player.target_position.y - player.pos.y) > 300: if 0 <= player.pos.x < 80: player.target_position.y = player.pos.y - direction * 100 player.target_position.x = 100 elif -80 < player.pos.x < 0: player.target_position.y = player.pos.y - direction * 100 player.target_position.x = -100 else: player.evaluation.close = False player.target_position.x = player.default_position.x player.target_position.y = player.default_position.y prox = self.game_logic.ball_handler.proximity if len(prox) > 0: enemies_in_proximity = [p for p in prox if p not in self.team] if len(enemies_in_proximity) > 0: self.game_logic.ball_handler.evaluation.close = True else: # other team has the ball for player in self.team: player.evaluation = player.evaluate_dist(self.game_logic.ballpos) if player.evaluation.go: player.target_position.x = self.game_logic.ballpos.x player.target_position.y = self.game_logic.ballpos.y else: if not player.is_goalee: player.target_position.x = player.default_position.x player.target_position.y = player.default_position.y else: other_dist = player.dist(self.game_logic.ball_handler.pos) pivot = {'x': 0, 'y': 0} pivot['y'] = player.default_position.y * 1.25 dx = self.game_logic.ball_handler.pos.x - pivot['x'] dy = self.game_logic.ball_handler.pos.y - pivot['y'] v2 = Vector(pivot, {'x': dx, 'y': dy}) v1 = Vector(player.default_position, {'x': 1, 'y': 0}) p = v1.intersects(v2) if p is not None: dist = player.dist(p) if True: # (dist < other_dist): player.target_position.x = p.x player.target_position.y = p.y if abs(self.game_logic.ball_handler.pos.x) < 100: player.target_position.x = self.game_logic.ball_handler.pos.x # Goalee shall cover the goal else: # No team has the ball for player in self.team: player.evaluation = player.evaluate_dist(self.game_logic.ballpos) player.evaluation.close = False if player.evaluation.go: player.target_position.x = self.game_logic.ballpos.x player.target_position.y = self.game_logic.ballpos.y else: player.target_position.x = player.default_position.x player.target_position.y = player.default_position.y v1 = Vector(player.pos, {'x': 1, 'y': 0}) v2 = Vector(self.game_logic.ballpos, self.game_logic.ball_speed) p = v1.intersects(v2) if p is not None: dist = player.dist(p) if dist < player.max_travel_dist: player.target_position.x = p.x player.target_position.y = p.y if (self.game_logic.ball_speed.magn() < 3 and self.game_logic.ballpos.dist(player.pos) < player.max_travel_dist): player.target_position.x = self.game_logic.ballpos.x player.target_position.y = self.game_logic.ballpos.y for i, player in enumerate(self.team): correction_needed = False if not player.controlled and not player.falling: msg = {} down_keys = {'a': False, 's': False, 'd': False, 'w': False, ' ': False} msg['pos'] = player.pos.round(2) msg['dir'] = rdz(player.dir, 2) if player.dist(player.target_position) > player.reach: dx = player.target_position.x - player.pos.x dy = player.target_position.y - player.pos.y down_keys = down_keys_from_direction(dx, dy) else: if (abs(player.pos.x - player.target_position.x) > self.correction_needed_threshold or abs(player.pos.y - player.target_position.y) > self.correction_needed_threshold): correction_needed = True player.pos.x = player.target_position.x player.pos.y = player.target_position.y msg['pos'] = player.target_position.round(2) msg['tdir'] = rdz(player.default_dir, 2) player.target_dir = rdz(player.default_dir, 2) msg['t'] = MsgTypes.PlayerInputUpdate msg['pi'] = i msg['tm'] = 1 if self.game_logic.team1 is self.team else 2 if player.health > 0: decision_time = self.current_time_stamp - player.last_decision_time_stamp decision_speed = self._reaction_time(player) input_changed = [False, down_keys] if (decision_time > decision_speed or self.game_logic.state == gl.GameStates.PreGame or self.game_logic.state == gl.GameStates.GetReady or self.game_logic.state == gl.GameStates.Goal): if player.evaluation and self.game_logic.state == gl.GameStates.Playing: if player.evaluation.close: if not down_keys[' ']: down_keys[' '] = True input_changed = [True, down_keys] input_changed = self.game_logic.update_player_input(player, misc.k2b(down_keys)) down_keys = misc.b2k(input_changed[1]) if player.evaluation and self.game_logic.state == gl.GameStates.Playing: if player.evaluation.close: if not down_keys[' ']: down_keys[' '] = True input_changed[0] = True if input_changed[0]: player.last_decision_time_stamp = self.current_time_stamp if input_changed[0] or correction_needed: msg['bk'] = misc.k2b(down_keys) self.arena.send_player_update(msg) class PlayerAI: def __init__(self, game_logic_instance, team, arena): self.team = team self.game_logic = game_logic_instance self.arena = arena