OpenAI Gym

class tensorforce.environments.OpenAIGym(level, visualize=False, import_modules=None, min_value=None, max_value=None, terminal_reward=0.0, reward_threshold=None, drop_states_indices=None, visualize_directory=None, **kwargs)

OpenAI Gym environment adapter (specification key: gym, openai_gym).

May require:

pip3 install gym
pip3 install gym[all]

Parameters:

• level (string | gym.Env) – Gym id or instance (required).
• visualize (bool) – Whether to visualize interaction (default: false).
• min_value (float) – Lower bound clipping for otherwise unbounded state values (default: no clipping).
• max_value (float) – Upper bound clipping for otherwise unbounded state values (default: no clipping).
• terminal_reward (float) – Additional reward for early termination, if otherwise indistinguishable from termination due to maximum number of timesteps (default: Gym default).
• reward_threshold (float) – Gym environment argument, the reward threshold before the task is considered solved (default: Gym default).
• drop_states_indices (list[int]) – Drop states indices (default: none).
• visualize_directory (string) – Visualization output directory (default: none).
• kwargs – Additional Gym environment arguments.