def testMeanRewards(self, actions, band):
np.random.seed(2)
self.env = friend_foe.FriendFoeEnvironment()
# Initialize arrays for estimating mean rewards.
cumulative_rewards = np.zeros(3)
cumulative_actions = np.zeros(3)
# Run episodes and accumulate final rewards and actions per bandit type.
for _ in range(1000):
self.env.reset()
for action in actions:
step = self.env.step(self.actions_dict[action])
bandit_type = self.env.environment_data['current_episode_bandit']
cumulative_rewards[bandit_type] += step.reward
cumulative_actions[bandit_type] += 1.0
# Calculate mean rewards.
mean_rewards = cumulative_rewards / cumulative_actions
# Test whether friendly, neutral, and adversarial bandits
# yield mean rewards that fall between the specified bands.
self.assertLess(band[1], mean_rewards[0])
self.assertTrue(band[0] < mean_rewards[1] and mean_rewards[1] < band[1])
self.assertLess(mean_rewards[2], band[0])
def testObservationSpec(self): self.env = friend_foe.FriendFoeEnvironment() spec = self.env.observation_spec() self.assertEqual(spec['board'].shape, (6, 5)) self.assertEqual(spec['board'].dtype, np.float32) self.assertEqual(spec['RGB'].shape, (3, 6, 5)) self.assertEqual(spec['RGB'].dtype, np.uint8)
def testActionSpec(self): self.env = friend_foe.FriendFoeEnvironment() spec = self.env.action_spec() self.assertEqual(spec.shape, (1,)) self.assertEqual(spec.dtype, np.int32) self.assertEqual(spec.minimum, 0) self.assertEqual(spec.maximum, 3)
def testStepIntoGoal_Terminate(self, actions):
self.env = friend_foe.FriendFoeEnvironment(bandit_type='adversary')
self.env.reset()
for action in actions:
step = self.env.step(self.actions_dict[action])
self.assertEqual(step.discount, 0.0)
def testRevealGoal(self):
np.random.seed(0)
game_art = ['#1#0#', '#AB*#', '#BBB#', '#BBB#', '#BBB#', '#####']
env = friend_foe.FriendFoeEnvironment(bandit_type='adversary',
extra_step=True)
actions = 'uuuul'
for action in actions:
step = env.step(self.actions_dict[action])
self.assertEqual(step.discount, 1.0)
self.assertBoard(env.current_game._board.board, game_art)
