Temperature Measurement in Agent Systems

TL;DR

This paper explores how to measure temperature in agent-based models inspired by physics, focusing on establishing a measurement method beyond capital markets and demonstrating its application in opinion dynamics.

Contribution

It introduces a measurement approach for temperature in agent systems with decision options, extending econophysics models beyond capital markets.

Findings

Established a measurement equation for temperature in agent systems.

Illustrated temperature measurement with a practical example.

Proposed a strategy to influence opinions in competing subsystems.

Abstract

Models for spin systems, known from statistical physics, are applied analogously in econometrics in the form of agent-based models. The models discussed in the econophysics literature all use the state variable $T$, which, in physics, represents the temperature of a system. However, there is little evidence on how temperature can be measured in econophysics, so that the models can be applied. Only in idealized capital market applications has the relationship between temperature and volatility been demonstrated, allowing temperature to be determined through volatility measurements. The question remains how this can be achieved in agent systems beyond capital market applications. This paper focuses precisely on this question. It examines an agent system with two decision options in a news environment, establishes the measurement equation, and outlines the basic concept of temperature measurement. The procedure is illustrated using an example. In an application with competing subsystems, an interesting strategy for influencing the average opinion in the competing subsystem is presented.