85 lines
2.4 KiB
Python
85 lines
2.4 KiB
Python
# import matplotlib
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# matplotlib.use('Agg')
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import matplotlib.pyplot as plt
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import numpy as np
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import pandas as pd
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from ReinforcmentLearning.game import start_try
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import conf
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def multipleTries(EPSILON, ALPHA, GAMMA):
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conf.show_game = False
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conf.plot_result = False
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wins_per_try = []
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for x in range(conf.AMOUNT_TRIES):
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cookies_per_run = oneTry(EPSILON, ALPHA, GAMMA)
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results_last_700 = cookies_per_run[-700:]
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wins_in_last_700 = sum(1 for result in results_last_700 if result == 20)
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win_probalitiy_last_700 = (wins_in_last_700 / 700)
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wins_per_try.append(win_probalitiy_last_700)
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# print(f"Finished try {x+1}\n")
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return wins_per_try
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def oneTry(EPSILON, ALPHA, GAMMA):
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"""
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state: (x_distance_to_ghost, y_distance_to_ghost, next_cookie_Direction)
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action: Direction
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q_value: (state, action)
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"""
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cookies_per_run, iterations = start_try(EPSILON, ALPHA, GAMMA)
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if conf.plot_result:
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wins = sum(1 for result in cookies_per_run if result == 20)
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print(f"Win percentage overall: {(wins/conf.AMOUNT_RUNS)*100}%")
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last_700_results = cookies_per_run[-700:]
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wins_in_last_700 = sum(1 for result in last_700_results if result == 20)
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win_percentage = (wins_in_last_700 / 700) * 100
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print(f"Win percentage in the last 700: {win_percentage:.2f}%\n")
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plot_results(cookies_per_run, iterations)
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return cookies_per_run
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def plot_results(cookies_per_run, iterations):
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wins = []
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losses = []
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win_count = 0
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for i, r in enumerate(cookies_per_run):
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if r == 20:
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win_count += 1
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wins.append(win_count)
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losses.append((i + 1) - win_count) # Losses count down from top
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# Create figure with 2 subplots (wins/losses and iterations)
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fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(10, 8))
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# Plot 1: Wins vs Losses
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ax1.plot(range(1, len(wins)+1), wins, 'b-', linewidth=1.5, label='Wins')
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ax1.plot(range(1, len(losses)+1), losses, 'orange', linewidth=1.5, label='Losses')
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ax1.set_xlabel('Attempt')
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ax1.set_ylabel('Count')
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ax1.set_title('Wins vs Losses Over Time')
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ax1.legend()
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# Plot 2: Iterations per run
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ax2.plot(range(1, len(iterations)+1), iterations, 'g-', linewidth=1.5)
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ax2.set_xlabel('Run Number')
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ax2.set_ylabel('Iterations')
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ax2.set_title('Iterations per Run')
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plt.tight_layout()
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plt.show() |