Struct ReinforcementLearning 

pub struct ReinforcementLearning { /* private fields */ }

Reinforcement learning with quantum circuit

Implementations

impl ReinforcementLearning

pub fn new() -> Self

Creates a new quantum reinforcement learning agent

pub fn with_algorithm(self, rl_type: ReinforcementLearningType) -> Self

Sets the reinforcement learning algorithm type

pub fn with_state_dimension(self, state_dim: usize) -> Self

Sets the state dimension

pub fn with_action_dimension(self, action_dim: usize) -> Self

Sets the action dimension

pub fn with_learning_rate(self, learning_rate: f64) -> Self

Sets the learning rate

pub fn with_discount_factor(self, discount_factor: f64) -> Self

Sets the discount factor

pub fn with_exploration_rate(self, exploration_rate: f64) -> Self

Sets the exploration rate

Trait Implementations

impl Clone for ReinforcementLearning

fn clone(&self) -> ReinforcementLearning

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for ReinforcementLearning

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl QuantumAgent for ReinforcementLearning

fn get_action(&self, state: &Array1<f64>) -> Result<usize>

Gets an action for a given state

fn update( &mut self, _state: &Array1<f64>, _action: usize, _reward: f64, _next_state: &Array1<f64>, _done: bool, ) -> Result<()>

Updates the agent based on a reward

fn train(&mut self, env: &mut dyn Environment, episodes: usize) -> Result<f64>

Trains the agent on an environment

fn evaluate(&self, env: &mut dyn Environment, episodes: usize) -> Result<f64>

Evaluates the agent on an environment