schola.ray.env.BaseEnv
class schola.ray.env.BaseEnv(unreal_connection, verbosity=0)
: Bases: BaseEnv
A Ray RLlib environment that wraps a Schola environment.
Parameters: : - unreal_connection (UnrealConnection) – The connection to the Unreal Engine environment.
- verbosity (int, default=0) – The verbosity level for the environment.
unwrapped : The underlying multi-agent environment.
Type: : MultiAgentEnv
last_reset_obs : The observations recorded during the last reset.
Type: : Dict[int,Dict[str,Any]]
last_reset_infos : The info dict recorded during the last reset.
Type: : Dict[int,Dict[str,str]]
Methods
__init__(unreal_connection[, verbosity]) | |
get_agent_ids() | Return the agent ids for the sub_environment. |
get_sub_environments([as_dict]) | Return a reference to the underlying sub environments, if any. |
last() | Returns the last observations, rewards, done- truncated flags and infos … |
poll() | Poll the environment for the next observation, reward, termination, info and any off_policy_actions (Currently Unused). |
send_actions(action_dict) | Called to send actions back to running agents in this env. |
stop() | Releases all resources used. |
to_base_env([make_env, num_envs, …]) | Converts an RLlib-supported env into a BaseEnv object. |
try_render([env_id]) | Tries to render the sub-environment with the given id or all. |
try_reset([env_id, seed, options]) | Attempt to reset the sub-env with the given id or all sub-envs. |
try_restart([env_id]) | Attempt to restart the sub-env with the given id or all sub-envs. |
Attributes
action_space | The action space for the environment. |
num_envs | The number of sub-environments in the wrapped environment. |
observation_space | The observation space for the environment. |
__init__(unreal_connection, verbosity=0) : Parameters: : - unreal_connection (UnrealConnection)
- verbosity (int)
property action_space*: DictSpace* : The action space for the environment.
Returns: : The action space for the environment
Return type: : DictSpace
property num_envs*: int* : The number of sub-environments in the wrapped environment.
Returns: : The number of sub-environments in the wrapped environment.
Return type: : int
property observation_space*: DictSpace* : The observation space for the environment.
Returns: : The observation space for the environment.
Return type: : DictSpace
poll() : Poll the environment for the next observation, reward, termination, info and any off_policy_actions (Currently Unused).
Returns: : - observations (EnvAgentIdDict[Dict[str,Any]]) – A dictionary, keyed by the environment and agent Id, containing the observations for each agent.
- rewards (EnvAgentIdDict[float]) – A dictionary, keyed by the environment and agent Id, containing the reward for each agent.
- terminateds (EnvAgentIdDict[bool]) – A dictionary, keyed by the environment and agent Id, containing the termination flag for each agent.
- truncateds (EnvAgentIdDict[bool]) – A dictionary, keyed by the environment and agent Id, containing the truncation flag for each agent.
- infos (EnvAgentIdDict[Dict[str,str]]]:) – A dictionary, keyed by the environment and agent Id, containing the information dictionary for each agent.
- off_policy_actions (EnvAgentIdDict[Any]) – A dictionary, keyed by the environment and agent Id, containing the off-policy actions for each agent. Unused.
Return type: : Tuple[Dict[int, Dict[int, Dict[str, Any]]], Dict[int, Dict[int, float]], Dict[int, Dict[int, bool]], Dict[int, Dict[int, bool]], Dict[int, Dict[int, Dict[str, str]]], Dict[int, Dict[int, Any]]]
send_actions(action_dict) : Called to send actions back to running agents in this env.
Actions should be sent for each ready agent that returned observations in the previous poll() call.
Parameters: : action_dict (Dict[int, Dict[int, Dict[str, Any]]]) – Actions values keyed by env_id and agent_id.
Return type: : None
stop() : Releases all resources used.
Return type: : None
try_reset(env_id=None, seed=None, options=None) : Attempt to reset the sub-env with the given id or all sub-envs.
If the environment does not support synchronous reset, a tuple of (ASYNC_RESET_REQUEST, ASYNC_RESET_REQUEST) can be returned here.
Note: A MultiAgentDict is returned when using the deprecated wrapper classes such as ray.rllib.env.base_env._MultiAgentEnvToBaseEnv, however for consistency with the poll() method, a MultiEnvDict is returned from the new wrapper classes, such as ray.rllib.env.multi_agent_env.MultiAgentEnvWrapper.
Parameters: : - env_id (int | None) – The sub-environment’s ID if applicable. If None, reset the entire Env (i.e. all sub-environments).
- seed (None | List[int] | int) – The seed to be passed to the sub-environment(s) when resetting it. If None, will not reset any existing PRNG. If you pass an integer, the PRNG will be reset even if it already exists.
- options (Dict[str, str] | None) – An options dict to be passed to the sub-environment(s) when resetting it.
Returns: : A tuple consisting of a) the reset (multi-env/multi-agent) observation dict and b) the reset (multi-env/multi-agent) infos dict. Returns the (ASYNC_RESET_REQUEST, ASYNC_RESET_REQUEST) tuple, if not supported.