Online Ordinal Problems: Optimality of Comparison-based Algorithms and their Cardinal Complexity
Nick Gravin, Enze Sun, Zhihao Gavin Tang

TL;DR
This paper investigates the potential advantage of cardinal algorithms over ordinal algorithms in online problems, establishing bounds and complexities, and demonstrating that in some cases, ordinal algorithms are nearly optimal.
Contribution
It provides a universal input distribution construction limiting the advantage of cardinal algorithms, introduces the concept of cardinal complexity, and analyzes specific problems like the game of googol.
Findings
Cardinal algorithms offer negligible advantage over ordinal algorithms with certain input distributions.
The input value range for some problems can be extremely large, up to a tower of exponents.
The game of googol has a relatively low cardinal complexity, making ordinal algorithms nearly optimal.
Abstract
We consider ordinal online problems, i.e., tasks that only require pairwise comparisons between elements of the input. A classic example is the secretary problem and the game of googol, as well as its multiple combinatorial extensions such as -secretary, -sided game of googol, ordinal-competitive matroid secretary. A natural approach to these tasks is to use ordinal algorithms that at each step only consider relative ranking among the arrived elements, without looking at the numerical values of the input. We formally study the question of how cardinal algorithms can improve upon ordinal algorithms. We give first a universal construction of the input distribution for any ordinal online problem, such that the advantage of any cardinal algorithm over the ordinal algorithms is at most for arbitrary small . As an implication, previous lower bounds…
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Taxonomy
TopicsOptimization and Search Problems · Auction Theory and Applications · Cryptography and Data Security
