Struct QuantumGame

pub struct QuantumGame {
    pub game_type: GameType,
    pub num_players: usize,
    pub players: Vec<QuantumPlayer>,
    pub game_circuit: Option<Array2<Complex64>>,
    pub payoff_matrices: Vec<Array2<f64>>,
    pub entanglement_operator: Option<Array2<Complex64>>,
}

Quantum game engine

Fields

game_type: GameType

Type of game

num_players: usize

Number of players

players: Vec<QuantumPlayer>

Players in the game

game_circuit: Option<Array2<Complex64>>

Quantum circuit for the game

payoff_matrices: Vec<Array2<f64>>

Payoff matrices (one for each player)

entanglement_operator: Option<Array2<Complex64>>

Entanglement operator (if applicable)

Implementations

impl QuantumGame

pub fn new(game_type: GameType, num_players: usize) -> Self

Create a new quantum game

pub fn add_player(&mut self, player: QuantumPlayer) -> QuantRS2Result<()>

Add a player to the game

pub fn set_payoff_matrix( &mut self, player_id: usize, payoffs: Array2<f64>, ) -> QuantRS2Result<()>

Set payoff matrix for a specific player

pub fn quantum_prisoners_dilemma() -> QuantRS2Result<Self>

Create quantum prisoner’s dilemma

pub fn quantum_coordination_game() -> QuantRS2Result<Self>

Create quantum coordination game

pub fn quantum_auction(num_bidders: usize) -> QuantRS2Result<Self>

Create quantum auction mechanism

pub fn play_game(&mut self) -> QuantRS2Result<GameOutcome>

Play the quantum game and return outcome

pub fn find_quantum_nash_equilibria( &mut self, ) -> QuantRS2Result<Vec<GameOutcome>>

Find quantum Nash equilibria using iterative algorithm

pub fn quantum_advantage(&mut self) -> QuantRS2Result<f64>

Compute quantum advantage over classical game

Trait Implementations

impl Clone for QuantumGame

fn clone(&self) -> QuantumGame

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for QuantumGame

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

Formats the value using the given formatter.