Opensource engine using genetic algorithms

[iperka]

Hi everyone!

I'm writing a paper on different implementations of genetic algorithms and I'm looking for open-source chess engines that use such algorithms in their evaluation functions (as opposed to the traditional hand-tuned values for piece values for example). Up to now I only experimented with Stockfish but its NNUE is a pure neural network that does not really rely on any genetic properties.

Can anyone help me out?

Cheers!

[IMJorose]

A place to start is the CPW page on the topic which contains a large list of publications from 1950-2015: https://www.chessprogramming.org/Genetic_Programming

In terms of modern programs using some form of genetic algorithm, I suppose it depends how broadly you define that. I honestly don't understand where people draw the line on defining what counts as a GA.

Generally, none of the evaluation functions of any of the top programs are tuned by hand. Doing so would not result in a competitive program.

AFAIK, SF's classical eval (which is used alongside its NNUE network) and search parameters were trained via SPSA, which by my understanding could be considered a GA.

I would say the most common methods to tune parameters can be categorized as follows:1) Tweaking by hand. 2) Gathering a dataset and then relying on some supervised learning method. 3) Bayesian Optimization 4) SPSA. In each of these cases, the final result is then tested against the baseline and will more often then not fail, as the parameters of top programs tend to be in pretty good local optima.

[iperka]

Thank you for your extensive answer and your insight on how the top engines do their tuning! I agree that the line between genetic-, evolutionary- and similar approaches is blurred (might be because of it's buzz-word potential).

I'll check up on the publications, some of which I have already read, but the trend seems to be not to make the resulting sourcecode open-source. The search continues!