hstrat: a Python Package for phylogenetic inference on
distributed digital evolution populations

Digital evolution systems instantiate evolutionary processes over populations of virtual agents in silico. These programs can serve as rich experimental model systems. Insights from digital evolution experiments expand evolutionary theory, and can often directly improve heuristic optimization techniques (Hernandez, Lalejini, & Dolson, 2022a; Hernandez, Lalejini, & Ofria, 2022). Perfect observability, in particular, enables in silico experiments that would be otherwise impossible in vitro or in vivo. Notably, availability of the full evolutionary history (phylogeny) of a given population enables very powerful analyses (Dolson & Ofria, 2018; Hernandez, Lalejini, & Dolson, 2022b; Shahbandegan et al., 2022).