Manipulation of individual judgments in the quantitative pairwise comparisons method

TL;DR

This paper explores how experts' judgments in pairwise comparison decision-making can be manipulated through bribery, proposing algorithms to identify and defend against such manipulations.

Contribution

It introduces a framework for understanding manipulation in pairwise comparisons and presents algorithms to detect and counteract bribery-based attacks.

Findings

Algorithms for manipulation detection

Framework for analyzing expert bribery

Insights into defending decision-making processes

Abstract

Decision-making methods very often use the technique of comparing alternatives in pairs. In this approach, experts are asked to compare different options, and then a quantitative ranking is created from the results obtained. It is commonly believed that experts (decision-makers) are honest in their judgments. In our work, we consider a scenario in which experts are vulnerable to bribery. For this purpose, we define a framework that allows us to determine the intended manipulation and present three algorithms for achieving the intended goal. Analyzing these algorithms may provide clues to help defend against such attacks.