diff --git a/ttt_learn.py b/ttt_learn.py
new file mode 100644
index 0000000..db85ab7
--- /dev/null
+++ b/ttt_learn.py
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+# A state is a dictionary with two keys, "board" and "player." Here's an example:
+# 
+# {
+#     "board": [None, None, "X", None, "O", None, "X", "O", None],
+#     "player": "X",
+# }
+
+
+def get_next_state(state, action):
+    """Returns the state which would result from taking an action at a particular state. 
+    """
+    if state["board"][action] is not None:
+        raise ValueError(f"Action {action} is illegal at state {state}; the space is occupied.")
+    new_board = state["board"].copy()
+    new_board[action] = state["player"]
+    new_player = get_opponent(state["player"])
+    return {
+        "board": new_board,
+        "player": new_player,
+    }
+
+def get_actions(state):
+    """Given a board state, returns a dictionary whose keys are possible actions and whose 
+    values are the resulting state from each action. If the game is over, returns an empty
+    dictionary because no further moves are possible.
+    """
+    if is_over(state):
+        return {}
+    else:
+        actions = {}
+        for i in range(9):
+            if state["board"][i] is None:
+                actions[i] = get_next_state(state, i)
+        return actions
+
+def choose_best_action(state):
+    """Given a state, returns the best action, its resulting state, and that state's value.
+    For each possible action, we find the value of the resulting state. 
+    Then, if the player is 'X', choose the action corresponding to the highest
+    value. If the player is 'O', choose the action corresponding to the lowest
+    value. 
+    """
+    actions = get_actions(state)
+    values_and_actions = [[get_value(result), action] for action, result in actions.items()]
+    if state["player"] == "X":
+        value, action = max(values_and_actions)
+    else:
+        value, action = min(values_and_actions)
+    return action, actions[action], value
+        
+def get_value(state, depth=0, debug=False):
+    """Determines the value of the state.
+    """
+    if is_win(state, state["player"]):
+        return 1
+    elif is_win(state, get_opponent(state["player"])):
+        return -1
+    elif is_draw(state):
+        return 0
+    else:
+        action, result, value = choose_best_action(state)
+        return value
+        
+
+# ================================== HELPERS ==============================================
+
+def get_opponent(player):
+    "Returns 'X' when player is 'O' and 'O' when player is 'X'"
+    if player == 'X':
+        return 'O'
+    elif player == 'O':
+        return 'X'
+    else:
+        raise ValueError(f"Unrecognized player {player}")
+
+def is_over(state):
+    "Returns True if the game is over"
+    return is_draw(state) or is_win(state, 'X') or is_win(state, 'O')
+
+def is_draw(state):
+    "Returns True if the game ended in a draw."
+    for space in state["board"]:
+        if space is None:
+            return False
+    return True
+    
+def is_win(state, player):
+    "Returns True if `player` has won the game."
+    win_lines = [[0,1,2], [3,4,5], [6,7,8], [0,3,6], [1,4,7], [2,5,8], [0, 4, 8], [2, 4, 6]]
+    for a, b, c in win_lines:
+        if state["board"][a] == player and state["board"][b] == player and state["board"][c] == player:
+            return True
+    return False