It sounds somehow related to Statistical Relational Learning (see, e.g.,
Pedro Domingos' book http://www.cs.umd.edu/srl-book/).

Best!
Sergio


On Sat, Jan 18, 2014 at 5:57 PM, YKY (Yan King Yin, 甄景贤) <
[email protected]> wrote:

> On Wed, Jan 15, 2014 at 7:29 PM, Russell Wallace <
> [email protected]> wrote:
>
>> I saw your post. I don't have an opinion about the geometry of mind, but
>> you're still on the list :)
>>
>
>
> Thanks =)  Well, to explain why we're interested in the geometry of mind...
>
> In logic-based AGI, the KB is a collection of logic formulas.  We may try
> to organize this KB with a hierarchical (ie, tree) structure, somewhat akin
> to a library catalog of books.  That is more or less standard classical AI
> stuff (although I'd argue that no one has yet built such a complete system
> with all the ingredients right).
>
> The geometry of mind concerns what happens when we try to map the logic
> formulas into a mathematical "space".  That has more meaning than a mere
> collection of formulas (ie, a set).  If the set has "neighborhoods", we
> have a topology.  If this topology has a distance metric, then we have a
> "geometry".  If the distances varies continuously, we have a differential
> geometry (or "manifold").
>
> Knowing the spatial structure of the "mind" (ie the KB), may present new
> methods for optimization, because mathematics offer almost inexhaustible
> tricks that can be applied to geometric space.  At least that's the hope.
>  That's why I (and Ben, it seems) are interested in conceptual geometry....
>
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