pneuma-pygame/main.py

84 lines
2.7 KiB
Python
Raw Normal View History

2023-11-23 15:37:02 +00:00
import random
import torch as T
import numpy as np
import matplotlib.pyplot as plt
2023-11-19 03:27:47 +00:00
from game import Game
2023-11-17 02:19:03 +00:00
from tqdm import tqdm
2023-11-19 03:27:47 +00:00
from os import environ
environ['PYGAME_HIDE_SUPPORT_PROMPT'] = '1'
2023-11-23 15:37:02 +00:00
random.seed(1)
np.random.seed(1)
T.manual_seed(1)
2023-11-23 15:37:02 +00:00
n_episodes = 1000
game_len = 10000
2023-11-17 02:19:03 +00:00
2023-11-23 15:37:02 +00:00
figure_file = 'plots/score.png'
2023-11-17 02:19:03 +00:00
2023-11-23 15:37:02 +00:00
game = Game()
agent_list = [0 for _ in range(game.max_num_players)]
score_history = np.zeros(
shape=(game.max_num_players, n_episodes))
best_score = np.zeros(game.max_num_players)
avg_score = np.zeros(game.max_num_players)
for i in tqdm(range(n_episodes)):
# TODO: Make game.level.reset_map() so we don't __init__ everything all the time (such a waste)
if i != 0:
game.level.__init__(reset=True)
# TODO: Make game.level.reset_map() so we don't pull out and load the agent every time (There is -definitevly- a better way)
for player in game.level.player_sprites:
for agent in agent_list:
player.agent = agent_list[player.player_id]
player.stats.exp = score_history[player.player_id][i-1]
agent_list = [0 for _ in range(game.max_num_players)]
for j in range(game_len):
if not game.level.done:
game.run()
game.calc_score()
2023-11-17 02:19:03 +00:00
for player in game.level.player_sprites:
2023-11-23 15:37:02 +00:00
if player.is_dead():
agent_list[player.player_id] = player.agent
player.kill()
2023-11-19 03:27:47 +00:00
2023-11-23 15:37:02 +00:00
# if (j == game_len-1 or game.level.done) and game.level.enemy_sprites != []:
# for player in game.level.player_sprites:
# for enemy in game.level.enemy_sprites:
# player.stats.exp *= .95
else:
break
2023-11-23 15:37:02 +00:00
for player in game.level.player_sprites:
if not player.is_dead():
agent_list[player.player_id] = player.agent
exp_points = player.stats.exp
score_history[player.player_id][i] = exp_points
avg_score[player.player_id] = np.mean(
score_history[player.player_id])
if avg_score[player.player_id] > best_score[player.player_id]:
best_score[player.player_id] = avg_score[player.player_id]
print(f"Saving models for agent {player.player_id}...")
player.agent.save_models(actr_chkpt = f"player_{player.player_id}_actor", crtc_chkpt = f"player_{player.player_id}_critic")
print("Models saved ...\n")
2023-11-23 15:37:02 +00:00
print(
f"\nCumulative score for player {player.player_id}: {score_history[0][i]}\nAverage score for player {player.player_id}: {avg_score[player.player_id]}\nBest score for player {player.player_id}: {best_score[player.player_id]}")
2023-11-23 15:37:02 +00:00
plt.plot(score_history[0])
game.quit()
plt.show()