Hi All,

 it's my pleasure to share with you two libraries: darwin and algebolic.

Algebolic is a library for evolving mathematical expressions. You can use 
it to perform what's known as symbolic regression, where a symbolic 
mathematical expression is found that fits a given dataset. More generally, 
you can use it to evolve mathematical expressions that optimise any score 
function. The expressions are implemented so they can be very quickly 
evaluated, as can their derivatives which is useful in more advanced 
applications. We use it in my research lab, for example, to evolve laws of 
physics directly from data.

Repository: https://github.com/JonyEpsilon/algebolic
Getting started example: 
http://viewer.gorilla-repl.org/view.html?source=github&user=JonyEpsilon&repo=algebolic&path=ws/demo/intro.clj

Algebolic is powered by ...

Darwin is a flexible framework for programming genetic algorithms, aimed at 
research applications. It is representation agnostic, working just as well 
for simple GA examples as it does for complex genetic programming problems. 
It can be configured to perform both single- and multi-objective 
optimisation, including the SPEA2 algorithm. It has facility for adaptive 
evolution where the run parameters evolve in response to changes in the 
population.

Repository: https://github.com/JonyEpsilon/darwin
Getting started example: 
http://viewer.gorilla-repl.org/view.html?source=github&user=JonyEpsilon&repo=darwin&path=ws/demo.clj


Some of the code is "research-quality" and in particular the core data 
structures in Darwin are a bit suspect. And the documentation is a bit 
sparse in places. But it works and maybe someone will find it useful :-)

Enjoy!


Jony

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