Tag Archives: PLN

Why Hypergraphs?

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

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PLN forward chainer

I (Jared Wigmore aka JaredW) have recently implemented a general forward chainer for PLN. (See Forward and Backward chaining on Wikipedia). Joel had previously implemented a prototype forward chainer, but it only supported deduction. PLN has a wide variety of … Continue reading

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Visualizing PLN inference

Recently Jared Wigmore, a student of Waikato University, New Zealand, created a tool for visualizing PLN as part of a visualisation project. In my opinion, the BIT visualiser shows great promise as a tool for understanding the complexities of BIT … Continue reading

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Fun with first-order inference

Joel Pitt has done some experiments testing first-order PLN inference in OpenCog, on some very simple data. These experiments don’t use the indefinite probability formulas but rather the good old fashioned SimpleTruthValue PLN formulas. What they involve is using PLN … Continue reading

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