Overview

This page provides an overview of the API along with examples.

Make Predictions

The quantum prisoner's dilemma model (QPDM) generates predictions for three conditions:

1. Player 1 is told that player 2 defected
2. Player 1 is told that player 2 cooperated
3. Player 1 is not informed of the action of player 2

using QuantumPrisonersDilemmaModel
model = QPDM(;μd=.51, γ=2.09)
predict(model)

3-element Vector{Float64}:
 0.8057112841924796
 0.6487381658136033
 0.5652813506885033

Simulate Model

The code block below demonstrates how to generate simulated data from the model using rand. In the example, we will generate 100 simulated trials for each condition.

using QuantumPrisonersDilemmaModel
model = QPDM(;μd=.51, γ=2.09)
data = rand(model, 100)

3-element Vector{Int64}:
 88
 67
 61

Evaluate Log Likelihood

The log likelihood of data can be evaluated using logpdf. In the code block below, we generate simulated data and evaluate the logpdf:

using QuantumPrisonersDilemmaModel
model = QPDM(;μd=.51, γ=2.09)
n_trials = 100
data = rand(model, n_trials)
logpdf(model, n_trials, data)

-10.446363596913525