Add basic TTT

examples/random_tic_tac_toe.py

@@ -1,8 +1,8 @@
 import gym
 import numpy as np
-import gym_random_walk
+import gym_tic_tac_toe
 
-env = gym.make('random_walk-v0')
+env = gym.make('tic_tac_toe-v0')
 
 num_episodes = 20
 num_steps_per_episode = 200
@@ -10,14 +10,21 @@ num_steps_per_episode = 200
 collected_rewards = []
 for i in range(num_episodes):
     s = env.reset()
+    print (s)
     print ("starting new episode")
     env.render()
     print ("started")
     total_reward = 0
     done = False
+    om = 1
     for j in range(num_steps_per_episode):
-        a = np.random.randint(env.action_space.n)
+        a = env.action_space.sample()
+        print (a[0])
+        #sm = s['on_move']
+        #print (sm)
+        a = tuple((om, a[1]))
         s1, reward, done, _ = env.step(a)
+        om = -om
         env.render()
         total_reward += reward
         s = s1

gym_random_walk/__init__.py

@@ -1,10 +0,0 @@
-from gym.envs.registration import register
-
-register(
-    id='random_walk-v0',
-    entry_point='gym_random_walk.envs:RandomWalkEnv',
-)
-#register(
-#    id='foo-extrahard-v0',
-#    entry_point='gym_foo.envs:FooExtraHardEnv',
-#)

gym_random_walk/envs/__init__.py

@@ -1 +0,0 @@
-from gym_random_walk.envs.random_walk_env import RandomWalkEnv

gym_random_walk/envs/random_walk_env.py

@@ -1,36 +0,0 @@
-import gym
-from gym import error, spaces, utils
-from gym.utils import seeding
-import numpy as np
-
-class RandomWalkEnv(gym.Env):
-  metadata = {'render.modes': ['human']}
-
-  def __init__(self):
-    self.action_space = spaces.Discrete(2)
-    self.size = 6
-    #print("init")
-  def _step(self, action):
-    #print("step")
-    reward = 0
-    done = False
-    if (action == 0):
-       self.state -= 1
-    if (action == 1):
-        self.state += 1
-    if (self.state >= self.size):
-        reward = 1
-        done = True
-    if (self.state <= 0):
-        done = True
-    return np.array(self.state), reward, done, {}
-  def _reset(self):
-    #print("reset")
-    print("#self.size:",self.size)
-    self.state =  np.random.randint(1,self.size-1)
-    print("starting: ", self.state)
-  def _render(self, mode='human', close=False):
-    if close:
-        return
-    #print("render")
-    print("current state: ",self.state)

gym_tic_tac_toe/__init__.py

@@ -0,0 +1,6 @@
+from gym.envs.registration import register
+
+register(
+    id='tic_tac_toe-v0',
+    entry_point='gym_tic_tac_toe.envs:TicTacToeEnv',
+)

gym_tic_tac_toe/envs/__init__.py

@@ -0,0 +1 @@
+from gym_tic_tac_toe.envs.tic_tac_toe_env import TicTacToeEnv

gym_tic_tac_toe/envs/tic_tac_toe_env.py

@@ -0,0 +1,64 @@
+import gym
+from gym import spaces
+import numpy as np
+
+class TicTacToeEnv(gym.Env):
+    metadata = {'render.modes': ['human']}
+
+    def __init__(self):
+        self.action_space = spaces.Tuple((spaces.Discrete(2), spaces.Discrete(9)))
+        self.observation_space = spaces.Discrete(3)#Tuple(spaces.Discrete(3), spaces.Discrete(9))
+    def _step(self, action):
+        done = False
+        reward = 0
+
+        p, square = action
+        
+       # p = p*2 - 1
+        # check move legality
+        proposed = self.state['board'][square]
+        om = self.state['on_move']
+        print ("on move: ", om)
+        if (proposed != 0): # wrong player, not empty
+            print("illegal move ", action, ". (square occupied): ", square)
+            done = True
+            reward = -om # player who did NOT make the illegal move
+        if (p != om): # wrong player, not empty
+            print("illegal move  ", action, " not on move: ", p)
+            done = True
+            reward = -om # player who did NOT make the illegal move
+        else:
+            self.state['board'][square] = p
+            self.state['on_move'] = -p
+
+        # check game over
+        for i in range(3):
+            if (self.state['board'][i * 3] == p and self.state['board'][i*3 + 1] == p and self.state['board'][i*3+2] == 2):
+                reward = p
+                done = True
+                break
+            #TODO other cases
+                
+        return np.array(self.state), reward, done, {}
+    def _reset(self):
+        self.state = {}
+        self.state['board'] = [0,0,0,0,0,0,0,0,0]
+        self.state['on_move'] = 1
+        return self.state
+    def _render(self, mode='human', close=False):
+        if close:
+            return
+        print("on move: " , self.state['on_move'])
+        for i in range (9):
+            print (self.state['board'][i], end=" ")
+        print()
+    def move_generator(self):
+        moves = []
+        for i in range (9):
+            if (self.state.state['board'][i]== 0):
+                p = self.state.on_move
+                if (p == 2):
+                    p = -1
+                m = [p, i]
+                moves.append(m)
+                

setup.py

@@ -1,9 +1,9 @@
 from setuptools import setup
 from setuptools import find_packages
 
-setup(name='gym_random_walk',
+setup(name='gym_tic_tac_toe',
       version='0.0.1',
       install_requires=['gym'],
-      url="https://github.com/nczempin/gym-random-walk",
+      url="https://github.com/nczempin/gym-tic-tac-toe",
       packages=find_packages()
 )