Provide different policy for player 1 and -1
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@ -3,10 +3,21 @@ import numpy as np
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import gym_tic_tac_toe
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import random
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def random_plus_middle_move(moves, p):
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if ([p, 4] in moves):
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m = [p, 4]
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else:
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m = random_move(moves, p)
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return m
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def random_move(moves, p):
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m = random.choice(moves)
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return m
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env = gym.make('tic_tac_toe-v0')
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num_episodes = 20
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num_steps_per_episode = 200
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num_episodes = 2000
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num_steps_per_episode = 10
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collected_rewards = []
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for i in range(num_episodes):
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@ -22,22 +33,30 @@ for i in range(num_episodes):
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moves = env.move_generator()
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print ("moves: ", moves)
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if (not moves):
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print ("out of moves")
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break
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m = random.choice(moves)
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if (len(moves)==1):
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m = moves[0]
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else:
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if (om == 1):
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m = random_plus_middle_move(moves, om)
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else:
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m = random_move(moves, om)
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print ("m: ", m)
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a = env.action_space.sample()
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print (a[0])
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#sm = s['on_move']
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#print (sm)
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a = tuple((om, a[1]))
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# a = env.action_space.sample()
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# print (a[0])
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# #sm = s['on_move']
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# #print (sm)
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# a = tuple((om, a[1]))
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s1, reward, done, _ = env.step(m)
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om = -om
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env.render()
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total_reward += reward
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s = s1
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if done:
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print ("game over: ", reward)
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break
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collected_rewards.append(total_reward)
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print ("total reward ", total_reward, " after episode: ", j)
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print ("total reward ", total_reward, " after episode: ", i, ". steps: ", j+1)
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print ("average score: ", sum(collected_rewards) / num_episodes)
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print("#########")
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