On 3/2/20 12:57 PM, Alexander Gabriel wrote:
No, it typically doesn't need to execute the link it is doing inference
on, rather it runs inference trees constructed from inference rules
that
produces the target, including updating its TV. Whether this is fast or
slow depends on the inference trees, not so much the target.
I'm not sure I understand, don't the inference trees result from the
interaction between the target and the rulebase?
Yes, but that's a static interaction. Basically, in the case of backward
chaining, the target is syntactically unified with the conclusion of
some rule, then some simple inference tree like
premise_1
...
premises_n
|-
target
is created, then one of the premises is syntactically unified with
another rule to create a bigger inference tree, etc.
Every time an inference tree is created it is executed, and results are
collected, and returned the user at the end.
Nil
> If you add a type declaration (I believe the python bindings
allow you
> that), it should speed up the reasoning as well.
Most of the atoms I add are ConceptNodes (200-300 at the moment and
almost all of them are places), so restricting chaining to those doesn't
help me much. In any case I'm already doing that.
for instance the frog example show an example of variable
declaration in
a backward chainer query
https://github.com/opencog/ure/tree/master/examples/ure/frog#backward-chainer
<https://github.com/opencog/ure/tree/master/examples/ure/frog#backward-chainer>
Yes, that's the same kind of variable declaration that I use above. The
VariableList from the GetLink I also give to the backward chainer.
What happens for different variations of variable declarations provided
for the getlink and the backward chainer, I've detailed in the last post.
Best,
Alex
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