How to represent symbolic knowledge using real numbers - theory about neural networks and natural/analog computing?
No, probably not.  I think you're expecting too much from the current state of the art in word embeddings.  Word embeddings don't magically capture all semantic knowledge.  They don't reflect perfect understanding of the language.  Instead, they're just useful mappings where similar words often have similar embeddings.  Moreover, the way word embeddings are constructed has nothing to do with logical formulas.

I don't think you're going to find that word embeddings solve the problem of converting from natural language to formulas.

I don't know what would count as a general theory of encoding algorithms for you.  There are certainly multiple papers that propose different methods of constructing different word embeddings; you could read those to understand the state of the art.