Struct renforce::trainer::QLearner

pub struct QLearner<A: FiniteSpace> { /* fields omitted */ }

Represents an OnlineTrainer for Q-functions Uses the Q-learning algorithm

Methods

impl<A: FiniteSpace> QLearner<A>

fn new(action_space: A,
       gamma: f64,
       alpha: f64,
       train_period: TimePeriod)
       -> QLearner<A>

Returns a new QLearner with the given info

fn default(action_space: A) -> QLearner<A>

Creates a new QLearner with default gamma, alpha, and train_period

fn gamma(self, gamma: f64) -> QLearner<A>

Sets gamma field of self

fn alpha(self, alpha: f64) -> QLearner<A>

Sets alpha field of self

fn train_period(self, train_period: TimePeriod) -> QLearner<A>

Sets train_period field of self

Trait Implementations

impl<A: Debug + FiniteSpace> Debug for QLearner<A>

fn fmt(&self, __arg_0: &mut Formatter) -> Result

Formats the value using the given formatter.

impl<T, S: Space, A: FiniteSpace> OnlineTrainer<S, A, T> for QLearner<A> where T: QFunction<S, A> + Agent<S, A>

fn train_step(&mut self, agent: &mut T, transition: Transition<S, A>)

Performs one training iteration using the given transition

fn train(&mut self, agent: &mut T, env: &mut Environment<State=S, Action=A>)

Automatically trains the agent to perform well in the environment