How far are you supposed to go to get the 57% average? At first it had some success, but after 100+ presses its guesses were correct only 49% of the time.
> I keep thinking that his actual problem is that he doesn't seem to believe in the implications of the axiom of the excluded middle. [...] I wonder why he never talks about this – surely as a mathematician he should be aware of intuitionistic logic? (Or is it that as a computer science and linguistics wannabe, I am aware of it but many mathematicians aren't bothered to take a look?)
Heck, I know professional logicians (mostly model theorists) who have never seen intuitionistic logic, in any context, ever. That said, Norman does know a fair bit about intuitionistic logic and constructive mathematics, and even some type theory. He does not like the underlying philosophy any more than he likes classical mathematics.
> Gentzen style sequent calculus with the only axiom being modus ponens
Sidenote: a calculus where modus ponens is an axiom is definitely not a Gentzen-style sequent calculus.
There's "felfogni", which means "to understand" as well. Cf. English "to grasp" and German "auffassen". Confounder: the Hungarian word is quite likely to be a direct translation of the German version!
> The word understand would be "érteni", and I'm not sure it has any interesting roots other than "ér" meaning vein or stream (potentially, did you get its meaning / source?)
It's worth noting that "érint" (the verb "touch") appears to have the same root as "ért".
My coauthors and I used a nigh-identical technique [1] (see Section 2 Implementation) in 2015 to:
1. Optimize the Guava library for energy consumption,
2. By varying the implementations of data type interfaces,
3. Using a genetic algorithm,
4. and our results were presented in SSBSE 2015 and published in the conference proceedings.
Two years later, Basios et. al presented at the very same conference [2], where they
1. Optimize the Guava library for memory consumption,
2. By varying the implementations of data type interfaces,
3. Using a genetic algorithm,
4. and their results were presented in SSBSE 2017 and published in the conference proceedings.
I am overjoyed that Basios et al. managed to take this technique so far, and that they obtained such impressive results. I am disappointed, however, that our work still goes completely uncited and unacknowledged in their papers. Given that it involved the same library, the same techniques, the same family of algorithms and the same conference, this simply could not have slipped through the cracks of any literature review - especially since one of the authors was present and interacted with us at SSBSE 2015. I'd be happy to hear any explanation for this omission.