{'fraction_non_alphanumeric': 0.014947683109118086, 'fraction_numerical': 0.0, 'mean_word_length': 5.568627450980392, '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}}
A Computational Model of Analogical Problem Solving

This paper outlines a theory of analogical reasoning based on a process-model of problem solving by analogy and the hypothesis that problem solving and learning are inalienable, concurrent processes in the human cognitive system. The analogical problem solver exploits prior experience in solving similar problems, and, in the process, augments a hierarchically-structured epsiodic long term memory. An analogical transformation process is developed based on a modified version of Means-Ends Analysis in order to map past solutions from similar problems into solutions satisfying the requirements of the new problem.