Tag Archives: MachineLearning

I’ve recently been hacking on creating a new parser for the Link Grammar theory of natural language parsing. I want to couple parsing to machine learning (ML), to that I can use ML to learn natural languages. To do that, I need to place everything in a certain abstract data representation framework that allows graph rewrite rules, logical reasoning, and Bayesian probabilistic reasoning to be combined. This framework exists in OpenCog, but few people know or understand this. That this framework also has a firm foundation in model theory, category theory (even n-categories!) and type theory is even less well known. To explain all this, I just wrote a simple, easy introduction to all of these ideas, and how they come together. Follow the link for more. Continue reading →