HEROS Beta 0.1

Initial release of HEROS (Heuristic Evolutionary Rule Optimization System). This release pairs with the initial manuscript submission to GECCO 2025 including early analysis and comparison of HEROS to the scikit-ExSTraCS algorithm. This version of HEROS includes a two phase algorithm (run without alternation between phases), where Phase I focuses on the discovery and optimization of candidate rules and Phase II focuses on using a population of final rules discovered by Phase I to learn optimal accurate and compact rule-sets. Both phases of the algorithm are uniquely driven by respective Pareto-inspired multi-objective fitness functions. While the code in this release has been designed to accommodate discrete or quantitative features, as well as binary or multiclass outcomes, thus far we have only thoroughly debugged and evaluated it for discrete features and binary outcomes. Many improvements and expansions of this algorithm are planned for the future. This version of the code was originally completed on January 29th 2025.