Comment by kittikitti

I find that the "ruliological approach" is very similar to feasible mathematics by Jiatu Li (https://eccc.weizmann.ac.il/report/2025/086/). In the last section before the Personal Notes, "In effect, we’re seeing that theoretical computer science can be done not only “purely theoretically”—say with methods from traditional mathematics—but also “empirically”, finding results and developing intuition by doing explicit computational experiments and enumerations." Where regular mathematics is "purely theoretical" and "empirically" is what Jiatu Li also describes in his paper sometimes referred to reverse mathematics like from Quanta magazine.

I appreciated the great explanation of space complexity and it eludicated why some scientific authors don't include it in their analysis of algorithms. However, Wolfram found that "by successively investigating both larger inputs and longer runtimes, one can develop reasonable confidence that—at least most of the time—one is correctly identifying both cases that lead to halting, and ones that do not." There are exceptions like Machine 600720 that have exceptionally long runtimes but I gain a much better understanding about an algorithm if I'm provided the space complexity. It's still an open question in pure theory but it could be understood from empirical results.