AggregatedPolicy< PolicyType > Class Template Reference

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

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

Detailed Description

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

Template Parameters

PolicyType

The type of the child policy.

Definition at line 27 of file aggregated_policy.hpp.

Member Typedef Documentation

using ActionType = typename PolicyType::ActionType

Convenient typedef for action.

Definition at line 31 of file aggregated_policy.hpp.

Constructor & Destructor Documentation

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.

Definition at line 39 of file aggregated_policy.hpp.

Member Function Documentation

void Anneal ( )

inline

Exploration probability will anneal at each step.

Definition at line 63 of file aggregated_policy.hpp.

ActionType 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.

Definition at line 52 of file aggregated_policy.hpp.

References DiscreteDistribution::Random().

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

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