On the closest balanced game

TL;DR

This paper introduces a fast algorithm to find the closest balanced game to a given game with an empty core, demonstrating that as the number of players increases, the projected game’s core tends to be a singleton, leading to a new solution concept called the least square core.

Contribution

It proposes an efficient algorithm for projecting games onto the set of balanced games and provides mathematical proof of the asymptotic behavior of the core structure as players increase.

Findings

Probability of singleton core approaches 1 with more players

Number of facets with non-singleton core tends to 0 asymptotically

Introduces the least square core as a new solution concept

Abstract

Cooperative games with nonempty core are called balanced, and the set of balanced games is a polyhedron. Given a game with empty core, we look for the closest balanced game, in the sense of the (weighted) Euclidean distance, i.e., the orthogonal projection of the game on the set of balanced games. Besides an analytical approach which becomes rapidly intractable, we propose a fast algorithm to find the closest balanced game, avoiding exponential complexity for the optimization problem, and being able to run up to 20 players. We show experimentally that the probability that the closest game has a core reduced to a singleton tends to 1 when the number of players grow. We provide a mathematical proof that the proportion of facets whose games have a non-singleton core tends to 0 when the number of players grow, by finding an expression of the aymptotic growth of the number of minimal balanced collections. This permits to prove mathematically the experimental result. Consequently, taking the core of the projected game defines a new solution concept, which we call least square core due to its analogy with the least core, and our result shows that the probability that this is a point solution tends to 1 when the number of players grow.