Computer Science notes on abstract machines 

> this tool can use them for actual exhaustive universal search (to not consfuse with naive "universal" "search", broadly published; naive one skips solutions)

- Abstract machine is most fundamental

- lambdas and transform grammars are useful in NLP (as well as FP), but inc/dec/jmpnz machine is more fundamental and more meaningful (depsite all of them being complete), it operates directly on numbers.
- It is also more intuitive to decide termination automatically on such machine (reject useless programs), termination is decidable for fixed input (papers back it up, but only when you request physically meaningful, inferred not specified in advance mem-bound etc, so deeply hidden - somwhere in my chats too and and on my github)
- Actually termination is decidable (rather than "undecidabke semi-decidable") for any input (halting problem) - but it is a long academic drama story (did not find any papers, someone should have published though, 'use your mind' is better), despite a trivial algorithm, literally rejecting turing-church inifinite objects;
  > hint: nuances aside, one hav to know conversion between universal and existential quantifiers to built such decider; send me a bid compensating for my time wasted on heuristic solvers, I'll write the universal one in js, lol)
