context learn and recall

At the very heart of this project are two functions:
context.learn(a,b,c)
context.recall(a,b)

First thing to note is the context variable.
Every thing we learn is with respect to a particular context.
In one context, everything must be (sort of) self consistent (though the nature of superpositions means we can tolerate ambiguity/inconsistency somewhat).
In different context, well, they are fully independent, so you can define anything.

The convention to define context is this learn rule:
|context> => |context: a sample context>

Perhaps a small example, consider 2 shops with different closing times on Mondays:
|context> => |context: shop 1>
closing-time |monday> => |time: 5pm>

|context> => |context: shop 2>
closing-time |monday> => |time: 6pm>

Now, if these were defined in the same context, then the second closing-time rule would over-write the first. But since they are in different context, it is perfectly fine.

Next, I have the assumption that all knowledge can be represented by triples (a,b,c):
context.learn(a,b,c)
And context.recall(a,b) returns c.

Maybe this assumption is wrong, or not the entire picture, but we can certainly go a long way using it.

For example:
|context> => |context: shop 1>
has:
a = ""
b = "context"
c = "context: shop 1"

closing-time |monday> => |time: 5pm>
has:
a = "closing-time"
b = "monday"
c = "time: 5pm"

Currently in the project we only handle a few data-types for a,b,c (and I don't currently see the need to add any more).
a must be a string.
b is a string or a ket
c is a string (auto cast to a ket), a ket, a superposition, or a stored_rule

And the back-end for context.learn() and context.recall() is currently a convoluted hash-table. But it shouldn't be too hard to swap that out for something better (eg a database or something) if we have to.

That's it for now.

Update: I rewrote the context.learn() and context.recall() code. Much simpler, more memory efficient and faster than the old one. eg, converting the geonames 15000 cities data to sw format was a full 24 times faster with the new code. And this also means loading Moby synonyms or loading geonames cities 1000 into the console, and working with it, is now practical.

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updated: 19/12/2016
by Garry Morrison
email: garry -at- semantic-db.org