GridEngine

class curiosity_gym.core.gridengine.GridEngine(env_settings: EnvironmentSettings, render_settings: RenderSettings, env_objects: EnvironmentObjects, agent_pov: AgentPOV | str)

Abstract grid-based environment class that implements the gymnasium api.

Parameters:

• env_settings (EnvironmentSettings) – Object storing settings for the environment.

• render_settings (RenderSettings) – Object storing render settings that should be apllied when the environment is used.

• env_objects (EnvironmentObjects) – Object storing all grid objects that were placed in the environment.

• agent_pov (AgentPOV | str) – Object or string defining the observations and action spaces of the RL agent. Valid string values are ‘global’, ‘local_W’ and ‘forward_L_W’, where W and L are integers defining the width and length of the respective POV.

Methods

check_task	Check whether the main task of an environment has been completed by the agent.
close	Clean up the environment.
find_object	Get non-wall grid object at given position.
get_object_ids	Get ids for all grid object types.
get_state	Get the current state of the environment.
get_wrapper_attr	Gets the attribute name from the environment.
has_wrapper_attr	Checks if the attribute name exists in the environment.
heatmap	Display heatmap of position counts of the agent.
init_render	Initialise render objects.
load_walls	Convert array of positions to wall objects for environment.
render	Compute the render frames as specified by render_mode.
reset	Reset the environment to an initial internal state.
set_wrapper_attr	Sets the attribute name on the environment with value.
simulate	Simulate the state of the environment if a given action were taken.
step	Run one timestep of the environment’s dynamics using the agent actions.

Attributes

metadata	Metadata of the environment.
np_random	Returns the environment's internal _np_random that if not set will initialise with a random seed.
np_random_seed	Returns the environment's internal _np_random_seed that if not set will first initialise with a random int as seed.
render_mode	Render mode in which the environment is run.
spec
unwrapped	Returns the base non-wrapped environment.
reward_range	Range of rewards that can be obtained within one episode.
action_space	Space of possible actions a RL agent can choose from.
observation_space	Space of possible observations returned by the environment.