diff --git a/a_player.py b/a_player.py index 0b66539..4ddeab6 100644 --- a/a_player.py +++ b/a_player.py @@ -10,7 +10,6 @@ class APlayer(object): self.other_mark = 'X' self.state = None - self.state_last = None def set_debug(self, with_debug): pass @@ -22,10 +21,10 @@ class APlayer(object): state.reshape(state.size)[move] = self.mark return state - def reward(self, value): + def new_game(self): pass - def new_game(self): + def end_game(self, reward): pass def has_won(self, state: np.array): diff --git a/human_player.py b/human_player.py index 9adbe46..c7cdb4f 100644 --- a/human_player.py +++ b/human_player.py @@ -42,7 +42,7 @@ class HumanPlayer(APlayer): state_next = self.to_state(state.copy(), move) return state_next, has_moved - def reward(self, value): + def end_game(self, value): if value > 0: print(f"{self.name}, Du hast gewonnen, super!") else: @@ -57,4 +57,4 @@ if __name__ == '__main__': if not has_moved: break - p.reward(1.0) + p.end_game(1.0) diff --git a/machine_player.py b/machine_player.py index e065826..b386328 100644 --- a/machine_player.py +++ b/machine_player.py @@ -16,6 +16,7 @@ class MachinePlayer(APlayer): self.values = {} self.with_debug = False self.values = values + self.episode_history = None def set_debug(self, with_debug): self.with_debug = with_debug @@ -45,22 +46,30 @@ class MachinePlayer(APlayer): def set_value(self, state: np.array, value): self.values[self.to_key(state)] = value - def reward(self, value): + def end_game(self, value): self.set_value(self.state, value) + print(self.episode_history) def new_game(self): self.state = None - self.state_last = None + self.episode_history = [] - def move(self, state: np.array): - values = np.array([]) - # get possible move - moves = get_potential_moves(state) - if moves.size == 0: - return state, False + def learn_from_history(self): + pass + def calc_value(self, state: np.array, next_state: np.array): + v0 = self.get_value(state) + v1 = self.get_value(next_state) + d = v0 + self.params.alpha*(v1-v0) + if self.with_debug: + print(f"{self.mark}: Learned {d:0.3f}") + + return d + + def get_best_move(self, state: np.array, moves: np.array): best_move = None best_value = -1 + values = np.array([]) for move in moves: # create hypothetical next state state_next = self.to_state(state.copy(), move) @@ -71,6 +80,15 @@ class MachinePlayer(APlayer): best_move = move values = np.append(values, value) + return best_move, best_value, values + + def move(self, state: np.array): + # get possible move + moves = get_potential_moves(state) + if moves.size == 0: + return state, False + + best_move, best_value, values = self.get_best_move(state, moves) next_move = best_move is_exp = False # Randomly perform exploratory move @@ -79,26 +97,28 @@ class MachinePlayer(APlayer): next_move = moves[index] is_exp = best_move != next_move + # Finally create next state + next_state = self.to_state(state.copy(), next_move) + next_value = self.get_value(next_state) + + # Maintain history + self.episode_history.append((self.to_key(next_state), next_value, next_move, is_exp)) + if self.with_debug: print(f"{self.mark}: Values = {values}") print(f"{self.mark}: Moves = {moves+1}") print(f"{self.mark}: Best move = {best_move+1}") print(f"{self.mark}: Next move = {next_move+1}, is_exp={is_exp}") - if self.state is not None: - self.state_last = self.state.copy() - - self.state = self.to_state(state.copy(), next_move) - # Learn - if not is_exp and self.state_last is not None: - v0 = self.get_value(self.state_last) - v1 = self.get_value(self.state) - d = v0 + self.params.alpha*(v1-v0) + if not is_exp and self.state is not None: + d = self.calc_value(self.state, next_state) if d > 0: - self.set_value(self.state_last, d) + self.set_value(self.state, d) if self.with_debug: print(f"{self.mark}: Learned {d:0.3f}") - return self.state, True + self.state = next_state + + return next_state, True diff --git a/tic_tac_toe.py b/tic_tac_toe.py index f58d9eb..5bc4ec6 100644 --- a/tic_tac_toe.py +++ b/tic_tac_toe.py @@ -43,14 +43,14 @@ def play(player_provider: PlayerProvider, k_max=10000, with_debug=False): if not has_moved: if with_debug: print(f"{player.mark}: No more moves") - player.reward(0.0) - other_player.reward(0.0) + player.end_game(0.0) + other_player.end_game(0.0) run = False if player.has_won(state): if with_debug: print(f"{player.mark}: Has won the game") - player.reward(1.0) - other_player.reward(0.0) + player.end_game(1.0) + other_player.end_game(0.0) run = False other_player = player