mlpack::rl::AggregatedPolicy< PolicyType > Class Template Reference

#include <aggregated_policy.hpp>

Public Types
using	ActionType = typename PolicyType::ActionType
	Convenient typedef for action.

Public Member Functions
	AggregatedPolicy (std::vector< PolicyType > policies, const arma::colvec &distribution)
ActionType	Sample (const arma::colvec &actionValue, bool deterministic=false)
	Sample an action based on given action values. More...
void	Anneal ()
	Exploration probability will anneal at each step.

Detailed Description

template<typename PolicyType>
class mlpack::rl::AggregatedPolicy< PolicyType >

Template Parameters

PolicyType

The type of the child policy.

Constructor & Destructor Documentation

AggregatedPolicy()

template<typename PolicyType >

mlpack::rl::AggregatedPolicy< PolicyType >::AggregatedPolicy ( std::vector< PolicyType >  policies, const arma::colvec &  distribution  )

inline

Parameters

policies	Child policies.
distribution	Probability distribution for each child policy. User should make sure its size is same as the number of policies and the sum of its element is equal to 1.

Member Function Documentation

Sample()

template<typename PolicyType >

ActionType mlpack::rl::AggregatedPolicy< PolicyType >::Sample ( const arma::colvec &  actionValue, bool  deterministic = false  )

inline

Sample an action based on given action values.

Parameters

actionValue	Values for each action.
deterministic	Always select the action greedily.

Returns

Sampled action.

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

• src/mlpack/methods/reinforcement_learning/policy/aggregated_policy.hpp