In my insights, logical formulas are merely yet another form by which we
can process some reasoning in a certain, more or less well understood way.
But, beside logic, I can imagine other forms of simulating human thoughts
(take Lambda calculus for example). Moreover, even almighty logic has many
forms like classical, fuzzy, modal, Bayesian, and who knows what other
forms.

On the opposite part of the communication chain, we have our natural
language that also comes in many flavors that are different in many ways.
There can also exist other ways for us to send or receive informations, but
I believe they can all be reduced to one dimensional streams of data.

So, I concluded that what I need for making a communication between a
machine and a human is a set of translating rules that interchange
informations between us. I came up with:

   1. a syntax definition part that can define both human, and more or less
   hi-level language built into a machine
   2. an operator for translating between those two.

For syntax definition I picked up some sort of context free grammar
language, and for a translation operator I chose a classic functional
language elements for defining functions and applying parameters. It turned
out that the grammar language and the translation operators complement each
other, making their disadvantages vanish in an extent I'm aware of.
Thinking further, it really doesn't matter what happens at the ends of the
communication chain, as long as we have a tool for translating between
those two, but there were some people that disagreed with this thought.

- ivan v.-


2017-12-05 23:12 GMT+01:00 Alex <[email protected]>:

> i.e. all the grammars in which I have interest have the common feature -
> capability of the grammatical framework to transform the natural language
> sentence in the logical formula that gives the meaning of this sentence.
>
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