Linas,
On 09/03/2016 08:54 AM, Linas Vepstas wrote:
I claim that inference is like parsing, and that algorithms suitable for
parsing can be transported and used for inference. I also claim that
these algorithms will all provide superior performance to
backward/forward chaining.
Until we can start to talk about inference as if it was a kind of
parsing, then I think we'll remain stuck, for a while.
It is inconvenient that I do not know LG well (I do know the basics
about parsing regular or context-free grammars but that's all).
I do have however some experience with automatic theorem proving, my
take is that no matter what abstraction you may come up with, it will
always suffer combinatorial explosion (as soon as the logic is
expressive enough). That is what I mean by linear or intuitionistic
logic being a hack, there is just no other way I can think of to tackle
that explosion than by using meta-learning so that it at least works
here on earth.
You say "of all of the algorithms that are known for performing
reasoning, forward/backward chaining are the worst and the slowest and
the lowest-performance of all", but that is not how FC and BC should be
thought of. First of all BC is just FC with a target driven inference
control. Second, FC is neither bad nor good, it all depends on the
control, right?
That is said, I totally like your multi-atomspace abstraction, looking
at confluence, etc. This is the way to go. I just fail to see how this
abstraction can help us simplify or optimize inference control. But I'm
certainly open to the idea.
Nil
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