mlpack::rl::MountainCar Class Reference

Implementation of Mountain Car task. More...

#include <mountain_car.hpp>

Classes
class	Action
	Implementation of action of Mountain Car. More...
class	State
	Implementation of state of Mountain Car. More...

Public Member Functions
	MountainCar (const size_t maxSteps=200, const double positionMin=-1.2, const double positionMax=0.6, const double positionGoal=0.5, const double velocityMin=-0.07, const double velocityMax=0.07, const double doneReward=0)
	Construct a Mountain Car instance using the given constant. More...
double	Sample (const State &state, const Action &action, State &nextState)
	Dynamics of Mountain Car. More...
double	Sample (const State &state, const Action &action)
	Dynamics of Mountain Car. More...
State	InitialSample ()
	Initial position is randomly generated within [-0.6, -0.4]. More...
bool	IsTerminal (const State &state) const
	This function checks if the car has reached the terminal state. More...
size_t	StepsPerformed () const
	Get the number of steps performed.
size_t	MaxSteps () const
	Get the maximum number of steps allowed.
size_t &	MaxSteps ()
	Set the maximum number of steps allowed.

Detailed Description

Implementation of Mountain Car task.

Constructor & Destructor Documentation

MountainCar()

mlpack::rl::MountainCar::MountainCar ( const size_t  maxSteps = 200, const double  positionMin = -1.2, const double  positionMax = 0.6, const double  positionGoal = 0.5, const double  velocityMin = -0.07, const double  velocityMax = 0.07, const double  doneReward = 0  )

inline

Construct a Mountain Car instance using the given constant.

Parameters

maxSteps	The number of steps after which the episode terminates. If the value is 0, there is no limit.
positionMin	Minimum legal position.
positionMax	Maximum legal position.
positionGoal	Final target position.
velocityMin	Minimum legal velocity.
velocityMax	Maximum legal velocity.
doneReward	The reward recieved by the agent on success.

Member Function Documentation

InitialSample()

State mlpack::rl::MountainCar::InitialSample ( )

inline

Initial position is randomly generated within [-0.6, -0.4].

Initial velocity is 0.

Returns

Initial state for each episode.

IsTerminal()

bool mlpack::rl::MountainCar::IsTerminal ( const State &  state ) const

inline

This function checks if the car has reached the terminal state.

Parameters

state

desired state.

Returns

true if state is a terminal state, otherwise false.

Sample() [1/2]

double mlpack::rl::MountainCar::Sample ( const State &  state, const Action &  action, State &  nextState  )

inline

Dynamics of Mountain Car.

Get reward and next state based on current state and current action.

Parameters

state	The current state.
action	The current action.
nextState	The next state.

Returns

reward, it's always -1.0.

Sample() [2/2]

double mlpack::rl::MountainCar::Sample ( const State &  state, const Action &  action  )

inline

Dynamics of Mountain Car.

Get reward based on current state and current action.

Parameters

state	The current state.
action	The current action.

Returns

reward, it's always -1.0.

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

• src/mlpack/methods/reinforcement_learning/environment/mountain_car.hpp