Matching games with partial information

TL;DR

This paper investigates various matching algorithms under partial information, examining their scaling, satisfaction distribution, and implications for market dynamics, including the effects of bounded rationality and information asymmetry.

Contribution

It introduces a generalized matching framework considering partial information and bounded rationality, and proposes a modified game modeling consumer-firm interactions in competitive markets.

Findings

Partial information affects satisfaction and scaling in matching games.

Self-searching and matchmaker strategies have different benefits under limited information.

Market-like dynamics emerge from the modified matching game.

Abstract

We analyze different ways of pairing agents in a bipartite matching problem, with regard to its scaling properties and to the distribution of individual ``satisfactions''. Then we explore the role of partial information and bounded rationality in a generalized {\it Marriage Problem}, comparing the benefits obtained by self-searching and by a matchmaker. Finally we propose a modified matching game intended to mimic the way consumers' information makes firms to enhance the quality of their products in a competitive market.