On Dec 31, 2012, at 1:21 PM, "Pascal J. Bourguignon" <[email protected]> 
wrote:
> 
> Now we know that a given formal system cannot be at the same time
> complete and consistent, but nothing prevents an automatic system to
> work with an incomplete system or an inconsistent system (or even a
> system that's both incomplete and inconsistent).
> 
> The only thing, is that sometimes you may reach conclusions such as 1=2,
> but if you expect them, you can deal with them.  We do everyday.
> 
> Notably, by modifying the mapping between the domain and the formal
> system: for different parts of the domain, you can use different formal
> systems, or avoid some axioms or theorems leading to a contradiction, to
> find some usable conclusion.


In chemical engineering, you design complex, dynamic systems that look like 
distributed computing systems in software, except that you replace bits with 
molecules. In the abstract, they are incredibly similar. I've often stated that 
my chemical engineering education was a valuable foundation for my later work 
in distributed and parallel systems.

Chemical engineering systems commonly have an interesting property: despite 
being built from a system of physics equations and carefully measured facts 
about reality, you can reduce that single set of inputs to multiple mutually 
inconsistent models of system behavior with material differences. The 
discipline has a rich set of heuristics and methods for dealing with complex 
distributed system problems that have significant internal contradictions, and 
with obviously good results, but you rarely see explicit analogues applied in 
software systems.

Computer science, perhaps due to its direct mathematical derivation, is not 
comfortable with an equivalent state of affairs where "1=2". Nonetheless, 
models of real complex systems tend to have this property.

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