Cf: Animated Logical Graphs • 37
http://inquiryintoinquiry.com/2020/08/22/animated-logical-graphs-37/

Re: Richard J. Lipton
https://rjlipton.wordpress.com/about-me/
::: Logical Complexity Of Proofs
https://rjlipton.wordpress.com/2020/08/19/logical-complexity-of-proofs/

Another dimension of proof style has to do with how much information
is kept or lost as the argument develops.  For the moment let's focus
on classical deductive reasoning at the propositional level.  Then we
can distinguish between "equational inferences", which keep all the
information represented by the input propositions, and "implicational
inferences", which permit information to be lost as the proof proceeds.

Information-Preserving vs. Information-Reducing Inferences
==========================================================

Implicit in Peirce's systems of logical graphs is the ability to use
equational inferences.  Spencer Brown drew this out and turned it to
great advantage in his revival of Peirce's graphical forms.  As it
affects "logical flow" this allows for bi-directional or reversible
flows, you might even say a "logical equilibrium" between two states
of information.

It is probably obvious when we stop to think about it, but
seldom remarked, that all the more familiar inference rules,
like modus ponens and resolution or transitivity, entail in
general a loss of information as we traverse their arrows or
turnstiles.

For example, the usual form of modus ponens takes us from knowing
p and p => q to knowing q but in fact we know more, we actually know
p and q.  With that in mind we can formulate two variants of modus ponens,
one reducing and one preserving the actual state of information, as shown
in the following figure.

Modus Ponens Variants
https://inquiryintoinquiry.files.wordpress.com/2020/08/modus-ponens-variants.png

There's more discussion of this topic at the following location.

* Propositional Equation Reasoning Systems : Computation and Inference as 
Semiosis
https://oeis.org/wiki/Propositional_Equation_Reasoning_Systems#Computation_and_inference_as_semiosis

To be continued ...

Regards,

Jon
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