Causal Analysis of an Agent-Based Model of Human Behaviour
Authored by Marcel Kvassay, Ladislav Hluchy, Peter Krammer, Bernhard Schneider
Date Published: 2017
DOI: 10.1155/2017/8381954
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Abstract
This article investigates causal relationships leading to emergence in
an agent-based model of human behaviour. A new method based on nonlinear
structural causality is formulated and practically demonstrated. The
method is based on the concept of a causal partition of a model variable
which quantifies the contribution of various factors to its numerical
value. Causal partitions make it possible to judge the relative
importance of contributing factors over crucial early periods in which
the emergent behaviour of a system begins to form. They can also serve
as the predictors of emergence. The time-evolution of their predictive
power and its distribution among their components hint at the deeper
causes of emergence and the possibilities to control it.
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