DiscreteActionEnv Class Reference

To use the dummy environment, one may start by specifying the state and action dimensions. More...

Classes
class	Action
	Implementation of discrete action. More...
class	State
	Implementation of state of the dummy environment. More...

Public Member Functions
State	InitialSample ()
	Dummy function to mimic initial sampling in an environment. More...
bool	IsTerminal (const State &) const
	Dummy function to find terminal state. More...
double	Sample (const State &, const Action &, State &)
	Dummy function to mimic sampling in an environment. More...

Detailed Description

To use the dummy environment, one may start by specifying the state and action dimensions.

Eg:

DiscreteActionEnv::State::dimension = 4;
DiscreteActionEnv::Action::size = 2;

Now the DiscreteActionEnv class can be used as an EnvironmentType in RL methods just as any other mlpack's implementation of gym environments.

Definition at line 32 of file env_type.hpp.

Member Function Documentation

InitialSample()

State InitialSample ( )

inline

Dummy function to mimic initial sampling in an environment.

Returns

the dummy state.

Definition at line 99 of file env_type.hpp.

References DiscreteActionEnv::State::State().

IsTerminal()

bool IsTerminal ( const State &  ) const

inline

Dummy function to find terminal state.

Parameters

*	(state) The current state.

Returns

It's of no use but so lets keep it false.

Definition at line 106 of file env_type.hpp.

Sample()

double Sample ( const State &  , const Action &  , State &    )

inline

Dummy function to mimic sampling in an environment.

Parameters

*	(state) The current state.
*	(action) The current action.
*	(nextState) The next state.

Returns

It's of no use so lets keep it 0.

Definition at line 89 of file env_type.hpp.

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The documentation for this class was generated from the following file:

• /home/ryan/src/mlpack.org/_src/mlpack-git/src/mlpack/methods/reinforcement_learning/environment/env_type.hpp