ast_toolbox.spaces.ast_spaces module¶

Class to define the action and observation spaces of an AST problem.

class ast_toolbox.spaces.ast_spaces.ASTSpaces[source]¶

Bases: object

Class to define the action and observation spaces of an AST problem.

Both the action_space and the observation_space should be a gym.spaces.Space type.

The action_space is only used to clip actions if ASTEnv is wrapped by the normalize env.

If using ASTEnv with blackbox_sim_state == True, observation_space should define the space for each simulation state variable. Otherwise, it should define the space of initial condition variables.

If using ASTEnv with fixed_init_state == False, the initial conditions of each rollout will be randomly sampled at uniform from the observation_space.

action_space¶

Returns a definition of the action space of the reinforcement learning problem.

Returns:	gym.spaces.Space – The action space of the reinforcement learning problem.

observation_space¶

Returns a definition of the observation space of the reinforcement learning problem.

Returns:	gym.spaces.Space – The observation space of the reinforcement learning problem.