{'fraction_non_alphanumeric': 0.01079136690647482, 'fraction_numerical': 0.0035971223021582736, 'mean_word_length': 5.258426966292135, '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}}
Research on Biped Robots Controller , Using Physical Simulation and Machine Learning Algorithms

Controlling a biped robot with a high degree of freedom to achieve stable movement patterns is an open and complex problem. With growing computational power of computer hardware, high resolution realtime simulation of such robot models becomes more and more applicable. This approach presents a physical simulation of a 19 degree of freedom real biped robot model. The aim is to explore and optimize different control models using machine learning algorithms.