Hi all, I would like to present for your consideration a project I am working on [1], which allows easy development of any formal theory expressible in a language described by a PEG. It provides a scalable rules engine in the form of a knowledge base that is initialized with a PEG grammar, and to which you can add as rules and facts the top productions of the grammar.
This implementation is in Python, on top of the excellent Parsimonious parser [2], by Erik Rose. The data (the rules and facts) are represented as a DAG, and all searches in the DAG are done by consulting Python dictionaries, so the time cost of adding new rules or facts should be essentially O(1) in the size of the knowledge base. My limited experiments (up to a few million rules + facts) seem promising. I would be very grateful for any feedback. 1.- https://pypi.org/project/syntreenet/ 2.- https://github.com/erikrose/parsimonious Best regards, -- Enrique Pérez Arnaud
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