Reducibility Among Fractional Stability Problems

TL;DR

This paper establishes the PPAD-completeness of several practical fractional stability problems through a series of reductions, introduces new concepts like preference games and personalized equilibria, and highlights a novel continuous-to-discrete reduction technique.

Contribution

It provides the first complexity classification for multiple fractional stability problems and introduces new reduction frameworks and concepts applicable in algorithmic game theory.

Findings

Proves PPAD-completeness of six fractional stability problems.

Develops a lattice of reductions connecting preference games and personalized equilibria.

Introduces a novel continuous-to-discrete reduction method.

Abstract

In this paper, we resolve the computational complexity of a number of outstanding open problems with practical applications. Here is the list of problems we show to be PPAD-complete, along with the domains of practical significance: Fractional Stable Paths Problem (FSPP) [21] - Internet routing; Core of Balanced Games [41] - Economics and Game theory; Scarf's Lemma [41] - Combinatorics; Hypergraph Matching [1]- Social Choice and Preference Systems; Fractional Bounded Budget Connection Games (FBBC) [30] - Social networks; and Strong Fractional Kernel [2]- Graph Theory. In fact, we show that no fully polynomial-time approximation schemes exist (unless PPAD is in FP). This paper is entirely a series of reductions that build in nontrivial ways on the framework established in previous work. In the course of deriving these reductions, we created two new concepts - preference games and personalized equilibria. The entire set of new reductions can be presented as a lattice with the above problems sandwiched between preference games (at the "easy" end) and personalized equilibria (at the "hard" end). Our completeness results extend to natural approximate versions of most of these problems. On a technical note, we wish to highlight our novel "continuous-to-discrete" reduction from exact personalized equilibria to approximate personalized equilibria using a linear program augmented with an exponential number of "min" constraints of a specific form. In addition to enhancing our repertoire of PPAD-complete problems, we expect the concepts and techniques in this paper to find future use in algorithmic game theory.