Automating decision making to help establish norm-based regulations

TL;DR

This paper presents a method for automating the decision-making process in establishing norm-based regulations by modeling relationships among norms and formulating the problem as a linear program.

Contribution

It introduces a novel approach to model norm relationships and preference criteria, enabling automated and optimal policy selection using linear programming.

Findings

Norm relationships include generalisation, exclusivity, and substitutability.

Decision problems can be encoded as linear programs for efficient solving.

The approach supports multiple preference criteria like power, cost, and moral values.

Abstract

Norms have been extensively proposed as coordination mechanisms for both agent and human societies. Nevertheless, choosing the norms to regulate a society is by no means straightforward. The reasons are twofold. First, the norms to choose from may not be independent (i.e, they can be related to each other). Second, different preference criteria may be applied when choosing the norms to enact. This paper advances the state of the art by modeling a series of decision-making problems that regulation authorities confront when choosing the policies to establish. In order to do so, we first identify three different norm relationships -namely, generalisation, exclusivity, and substitutability- and we then consider norm representation power, cost, and associated moral values as alternative preference criteria. Thereafter, we show that the decision-making problems faced by policy makers can be encoded as linear programs, and hence solved with the aid of state-of-the-art solvers.