Updated rewards and fixed formatting
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e57d826239
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32bff8b5c5
3 changed files with 4 additions and 8 deletions
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@ -161,7 +161,7 @@ class Player(pygame.sprite.Sprite):
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self.old_state_features = self.state_features
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self.reward = self.stats.exp
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# + self.stats.health/self.stats.stats['health'] - 1\
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+ self.stats.health/self.stats.stats['health'] - 1
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# - nearest_dist/np.sqrt(np.sum(self.map_edge))
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self.state_features = [
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1
level.py
1
level.py
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@ -294,7 +294,6 @@ class Level:
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if player.is_dead():
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print(f"\nPlayer {player.player_id} is dead\n")
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player.stats.exp = -10
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player.update()
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self.dead_players[player.player_id] = player.is_dead()
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self.done = True if (self.dead_players.all() == 1
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9
main.py
9
main.py
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@ -26,6 +26,7 @@ def main():
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chkpt_path, figure_path = folder_struct.setup_dirs()
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# Setup AI params
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n_episodes = parsed_args.n_episodes
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episode_length = parsed_args.ep_length
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n_agents = parsed_args.n_agents
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@ -38,8 +39,6 @@ def main():
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show_pygame = parsed_args.show_pg
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# Setup AI metrics
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# Setup parameter monitoring
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score_history = np.zeros(
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shape=(parsed_args.n_agents, parsed_args.n_episodes))
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@ -63,9 +62,6 @@ def main():
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time_alive = np.zeros(shape=(parsed_args.n_agents,
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parsed_args.n_episodes))
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# score_history, best_score, actor_loss, critic_loss, total_loss, entropy, advantage = metrics.generate(parsed_args)
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game = Pneuma(show_pg=show_pygame, n_players=parsed_args.n_agents)
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print("Initializing agents ...")
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@ -202,9 +198,10 @@ def main():
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metrics.plot_parameter('advantage', advantage, parsed_args.n_agents, figure_path)
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metrics.plot_avg_time(time_alive, parsed_args.n_agents, figure_path)
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# End of training session
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print("End of episodes.\
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\nExiting game...")
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\n Saving models and exiting game...")
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# Save models
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player.agent.save_models(
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