Adding a new algorithm

[umfundii]

Hi,

Thank you for providing this fantastic library. I'm interested in adding a new algorithm, specifically the 'cross-entropy method.'
Could you please provide an example or guidance on how to do this?

Thank you.

[BillHuang2001]

Yes, we currently have a simple guide on how to add a new algorithm. https://evox.readthedocs.io/en/latest/guide/advanced/3-custom-alg-pro.html#example
This guide will introduce the Algorithm class, which is used to implement new algorithms.

For your case, to implement a typical "cross-entropy method" (from wikipedia)

// Initialize parameters
μ := −6
σ2 := 100
t := 0
maxits := 100
N := 100
Ne := 10
// While maxits not exceeded and not converged
while t < maxits and σ2 > ε do
    // Obtain N samples from current sampling distribution
    X := SampleGaussian(μ, σ2, N)
    // Evaluate objective function at sampled points
    S := exp(−(X − 2) ^ 2) + 0.8 exp(−(X + 2) ^ 2)
    // Sort X by objective function values in descending order
    X := sort(X, S)
    // Update parameters of sampling distribution via elite samples                  
    μ := mean(X(1:Ne))
    σ2 := var(X(1:Ne))
    t := t + 1
// Return mean of final sampling distribution as solution
return μ

You will need to implement the following methods of the Algorithm class

• __init__
• setup initialize μ, σ2 here as the state of this algorithm, because these two are changing throughout the iterations.
• ask do SampleGaussian
• tell do sort, and update μ, σ2 in the state

I hope this helps.

[umfundii]

@BillHuang2001 Thanks, I will close this for now.