{'fraction_non_alphanumeric': 0.01763668430335097, 'fraction_numerical': 0.0, 'mean_word_length': 5.454545454545454, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Solving satisfiability in fuzzy logics with evolution strategies

Satisfiability in propositional logic is well researched and many approaches to checking and solving exist. In infinite-valued or fuzzy logics, however, there have only recently been attempts at developing methods for solving satisfiability. In this paper, we propose a new incomplete solver, based on a class of continuous optimization algorithms called evolution strategies. We show experimentally that our method is an important contribution to the state of the art in incomplete fuzzy-SAT solvers.