logpy

ave to (for efficiency or expressiveness.) (The paradigm hierarchy being: Logical/Relational >= Functional >= Imperative) I find myself pivoting from being an expert Python programmer to a tyro Prolog programmer. It's disorienting, exciting, it makes me giddy at moments. I'm already more productive, and it's easier to write bug-free code. In the particular case of implementing Joy in Python and in Prolog, I had previously learned about Logic Programing and Unification by studying an implementation of miniKanren in Python[1], so I knew what I was doing when implementing the type inference. There even came a moment when I realized that I should reimplement in Kanren or Prolog if I wanted to do things like propagate constraints ("value types", etc...) Then a link here on HN to "Logic Programming and Compiler Writing" by David H. D. Warren[2] finally pushed me to do it. I was in the middle of writing a compiler (to Python/Cython) for Joy and I realized that Warren's paper showed a better way. Reimplementing Joy in Prolog was as simple as typing in descriptions of the basic relations, which are then already executable. Something curious happened next. I went to reimplement the type inference code and when I had finished I realized that I had just reimplemented the interpreter. In other words, in Prolog, the interpreter and the type inferencer are the same thing. (Also, ten pages of Python code became one page of Prolog.) [1] https://github.com/logpy/logpy [2] https://news.ycombinator.com/item?id=17674859

nking that really has been automated. It's AI. (Not all that AI is or ever will be, but it counts.) Turing essentially made concrete the thought process of solving (some kinds of) math problems, noticed that the "atomic elements" of the process were a finite set, and designed a machine to automate those steps, so in a sense, computers have always been AI. > CLP(FD) stuff you posted isn't "just" unification, it needs additional powerful constraint solving algorithms behind it to work as well as it does. Yes, and the brain has powerful sensory systems attached to it. I think science has identified something like twenty-seven different human senses. These all supply "finite domains" to the reasoning system. The sensory systems are very active, and can function in "virtual" mode (aka imagination) to permit a kind of thinking by simulation (analogs.) Animals have this sort of thinking as well (that's why they can dream.) The linguistic/digital system reifies this fast primary mode thinking into slower rational thinking distinctions and reasoning, which is then used to build coherent models of the world which are then used to generate behavior. [2] If you codify that thinking process you get the unification algorithm. [1] https://github.com/logpy/logpy [2] ...and behavior generates new sensory inputs... The whole thing constitutes a feedback loop linking the real world with your subjective experience. Linguistic thinking permits direct modeling of recursion, which permits thinking about open-ended loops in behavior in a concrete way, which permits self-referential modification of the reasoning structures, enabling rapid innovation in behavior (aka "culture".) You're a cybernetic process that can become a Gödel machine.

same sort of puzzle as Sudoku, but much simpler. It's unfortunate that the solution and the solving proper (querying for the result) obscure the art of the puzzle-maker, eh? Thanks for the suggestion! I've incorporated it into the version in Github "gist": https://gist.github.com/calroc/603ed919bc814ccee10c1b3df6142... (I kept the more verbose query though, as I think the output is nicer. :-) YMMV)