Struct border_atari_env::util::test::RandomAgent

pub struct RandomAgent { /* private fields */ }

A random policy.

Implementations

impl RandomAgent

pub fn n_opts_steps(&self) -> usize

Returns the number of optimization steps;

Trait Implementations

impl<R: ReplayBufferBase> Agent<BorderAtariEnv<BorderAtariObs, BorderAtariAct, BorderAtariObsRawFilter<BorderAtariObs>, BorderAtariActRawFilter<BorderAtariAct>>, R> for RandomAgent

fn train(&mut self)

Set the policy to training mode.

fn eval(&mut self)

Set the policy to evaluation mode.

fn is_train(&self) -> bool

Return if it is in training mode.

fn opt(&mut self, buffer: &mut R) -> Option<Record>

Do an optimization step.

fn save<T: AsRef<Path>>(&self, _path: T) -> Result<()>

Save the agent in the given directory. This method commonly creates a number of files consisting the agent in the directory. For example, the DQN agent in border_tch_agent crate saves two Q-networks corresponding to the original and target networks.

fn load<T: AsRef<Path>>(&mut self, _path: T) -> Result<()>

Load the agent from the given directory.

impl Policy<BorderAtariEnv<BorderAtariObs, BorderAtariAct, BorderAtariObsRawFilter<BorderAtariObs>, BorderAtariActRawFilter<BorderAtariAct>>> for RandomAgent

type Config = RandomAgentConfig

Configuration of the policy.

fn build(config: Self::Config) -> Self

Builds the policy.

fn sample(&mut self, _: &Obs) -> Act

Sample an action given an observation.