Jared Wigmore

The OpenCog Brainwave article PLN forward chainer said

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 inference rules. They each require different sorts of input atoms, and so a forward (or backward) chainer for PLN needs to be able to find appropriate atoms for each inference rule.
 
There’s a new “pln fc” command, in the CogServer shell, which runs some FC inference.
 
Following is a general explanation of how it works. The idea is that each PLN Rule can provide templates for the Atoms it requires as input. In each inference step, the forward chainer picks a Rule, and then looks up a sequence of Atoms that match the input templates.
 
Here’s an example with DeductionRule, solving the classic “Mortal Socrates” problem, explained on the OpenCog wiki.
 
DeductionRule requires two Atoms, in the form:
 
(Inheritance A B)
(Inheritance B C)
 
which basically means, A is a B and B is a C. It then produces:
 
(Inheritance A C)
 
For the first argument, the forward chainer looks up any Atom that matches (Inheritance A B), that is, any InheritanceLink in the system. Suppose it finds “Socrates is a man”:
 
(Inheritance Socrates man)
 
Now it has A = Socrates and B = man. So to find the second argument, it looks for:
 
(Inheritance man C)
 
i.e. “man/men is/are <something>”. Suppose it finds “Men are mortal”:
 
(Inheritance man mortal)
 
Then it feeds these two premises into the DeductionRule, which produces:
 
(Inheritance Socrates mortal)

Jared Wigmore was the author of this article and is an OpenCog AI Researcher at Hong Kong Polytechnic University.
 
Jared earned his BCMS (Honors) in Computer Science and Cognitive Science at the University of Waikato, New Zealand in 2010.
 
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