1-2 years ago i went deep into different Concept theories (Classic, prototype, exemplar, Formal Concept Analysis, Cobweb algo, formal-semantics & logic+lambda, frame-semantics … etc)
Neither one is satisfying … currently I’d vote for Embodied image schemas, which is not clear how to implement.
If we go with HTM then I would think that image schemas concepts are grounded on sequence-of-sequences of sensory-motor programs.
NN uses pattern matching, which is static, cos and euclidean similarity i.e. wont work
A Concept is “recognized-sequence” !!
The other thing all theories get wrong is they are based on similarity, but there are no known Similarity measure that captures Concept-similarity.
The reason is that difference is the primary similarity is only meaningful in context and is asymetric.
Similarity is only possible across a measurable “dimension”, which is “revealed” only because there is difference .
Which means SDR overlap wont be the ultimate similarity there have to be some other way.