jaclearn.rl.envs package

Subpackages

• jaclearn.rl.envs.maze package
  • Submodules
  • jaclearn.rl.envs.maze.maze module
  • jaclearn.rl.envs.maze.taxi module
• jaclearn.rl.envs.nintendo package
  • Submodules
  • jaclearn.rl.envs.nintendo.mario module
• jaclearn.rl.envs.simple package
  • Submodules
  • jaclearn.rl.envs.simple.move_right module

Submodules

jaclearn.rl.envs.gym module

class jaclearn.rl.envs.gym.GymRLEnv(name, dump_dir=None, force_dump=False, state_mode='DEFAULT')

Bases: jaclearn.rl.env.SimpleRLEnvBase

gym

render(mode='human', close=False)

class jaclearn.rl.envs.gym.GymAtariRLEnv(name, *args, live_lost_as_eoe=True, **kwargs)

Bases: jaclearn.rl.envs.gym.GymRLEnv

class jaclearn.rl.envs.gym.GymPreventStuckProxy(other, max_repeat, action)

Bases: jaclearn.rl.env.ProxyRLEnvBase

jaclearn.rl.envs.gym_adapter module

class jaclearn.rl.envs.gym_adapter.DiscreteToMultiDiscrete(multi_discrete, options=None)

Bases: gym.spaces.discrete.Discrete

Adapter that adapts the MultiDiscrete action space to a Discrete action space of any size The converted action can be retrieved by calling the adapter with the discrete action discrete_to_multi_discrete = DiscreteToMultiDiscrete(multi_discrete) discrete_action = discrete_to_multi_discrete.sample() multi_discrete_action = discrete_to_multi_discrete(discrete_action)

It can be initialized using 3 configurations: Configuration 1) - DiscreteToMultiDiscrete(multi_discrete) [2nd param is empty] Would adapt to a Discrete action space of size (1 + nb of discrete in MultiDiscrete) where

• 0 returns NOOP [ 0, 0, 0, …]
• 1 returns max for the first discrete space [max, 0, 0, …]
• 2 returns max for the second discrete space [ 0, max, 0, …]
• etc.

Configuration 2) - DiscreteToMultiDiscrete(multi_discrete, list_of_discrete) [2nd param is a list] Would adapt to a Discrete action space of size (1 + nb of items in list_of_discrete) e.g. if list_of_discrete = [0, 2]

• 0 returns NOOP [ 0, 0, 0, …]
• 1 returns max for first discrete in list [max, 0, 0, …]
• 2 returns max for second discrete in list [ 0, 0, max, …]
• etc.

Configuration 3) - DiscreteToMultiDiscrete(multi_discrete, discrete_mapping) [2nd param is a dict] Would adapt to a Discrete action space of size (nb_keys in discrete_mapping) where discrete_mapping is a dictionnary in the format { discrete_key: multi_discrete_mapping } e.g. for the Nintendo Game Controller [ [0,4], [0,1], [0,1] ] a possible mapping might be;

> mapping = { > 0: [0, 0, 0], # NOOP > 1: [1, 0, 0], # Up > 2: [3, 0, 0], # Down > 3: [2, 0, 0], # Right > 4: [2, 1, 0], # Right + A > 5: [2, 0, 1], # Right + B > 6: [2, 1, 1], # Right + A + B > 7: [4, 0, 0], # Left > 8: [4, 1, 0], # Left + A > 9: [4, 0, 1], # Left + B > 10: [4, 1, 1], # Left + A + B > 11: [0, 1, 0], # A only > 12: [0, 0, 1], # B only, > 13: [0, 1, 1], # A + B > }