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<typenamePolicyType>
class mlpack::rl::AggregatedPolicy< PolicyType >
template
<
typename
PolicyType
>
- Template Parameters
-
PolicyType The type of the child policy.
Definition at line 27 of file aggregated_policy.hpp.
Member Typedef Documentation
◆ ActionType
| using ActionType = typename PolicyType::ActionType |
Convenient typedef for action.
Definition at line 31 of file aggregated_policy.hpp.
Constructor & Destructor Documentation
◆ AggregatedPolicy()
|
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
◆ Anneal()
|
inline |
Exploration probability will anneal at each step.
Definition at line 63 of file aggregated_policy.hpp.
◆ Sample()
|
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().
The documentation for this class was generated from the following file:
- /home/ryan/src/mlpack.org/_src/mlpack-git/src/mlpack/methods/reinforcement_learning/policy/aggregated_policy.hpp