10#ifdef MOOSE_LIBTORCH_ENABLED
47 virtual void execute()
override;
Reporter which saves the reward values from a Deep Reinforcement Learning controller trainer.
std::vector< Real > & _sample_average_reward
The per-sample average reward values which will be saved.
static InputParameters validParams()
Return the input parameters supported by this reporter.
virtual void finalize() override
Finalize the reporter.
LibtorchDRLControlTrainer & _trainer
The DRL trainer which computes the reward values.
std::vector< Real > & _sample_std_reward
The per-sample reward standard deviations which will be saved.
Real & _std_reward
The standard deviation of the reward values which will be saved.
virtual void initialize() override
Initialize the reporter.
virtual void execute() override
Update the reported reward statistics.
Real & _average_reward
The reward values which will be saved.
Fixed-horizon actor-critic trainer that collects trajectories from MOOSE reporters and runs a PPO upd...
const InputParameters & parameters() const
Interface for objects that need to use samplers.