# Agreement Functions for Distributed Computing Models

## TL;DR

This paper introduces agreement functions to characterize the computational capabilities of various distributed computing models, providing a unified framework to understand task solvability under different adversaries.

## Contribution

It presents a novel, simple characterization of distributed models using agreement functions, capturing the computability of a broad class of adversaries.

## Key findings

- Agreement functions precisely characterize task computability.
- The framework applies to a wide class of fair adversaries.
- Includes models with superset-closed and symmetric adversaries.

## Abstract

The paper proposes a surprisingly simple characterization of a large class of models of distributed computing, via an agreement function: for each set of processes, the function determines the best level of set consensus these processes can reach. We show that the task computability of a large class of fair adversaries that includes, in particular superset-closed and symmetric one, is precisely captured by agreement functions.