Laypersons often use the word "solution" in situations where an academic would say "method" or "approach": we did something useful, but it may not be the best p

Laypersons often use the word "solution" in situations where an academic would say "method" or "approach": we did something useful, but it may not be the best possible way. In pure math, "solution" means determining whether a logical statement is true or false. For example, in (asymptotic, worst-case) analysis of algorithms, the logical statements take the form "there exists an algorithm to compute X with asymptotic complexity O(f(n)), and no algorithm with lower complexity exists." These are crisp notions with no room for debate. In this competition, they defined "solved" as achieving 90% accuracy. This is somewhere in between the two definitions. It's technically a valid problem statement, but it can become obsolete in a weird way. If someone else solves the problem of achieving 95% accuracy, then suddenly the 90% solution doesn't look so good. Compare to e.g. sorting. If we add the requirement of a stable sort, it becomes a new problem. Stable sorting algorithms are not automatically "better" than unstable ones.