Researchers have long been interested in the role that norms can play in
governing agent actions in multi-agent systems. Much work has been done on
formalising normative concepts from human society and adapting them for the
government of open software systems, and on the simulation of normative
processes in human and artificial societies. However, there has been
comparatively little work on applying normative MAS mechanisms to understanding
the norms in human society.
This work investigates this issue in the context of international politics.
Using the GDELT dataset, containing machine-encoded records of international
events extracted from news reports, we extracted bilateral sequences of
inter-country events and applied a Bayesian norm mining mechanism to identify
norms that best explained the observed behaviour. A statistical evaluation
showed that the normative model fitted the data significantly better than a
probabilistic discrete event model.Comment: 16 pages, 2 figures, pre-print for International Workshop on
Coordination, Organizations, Institutions, Norms and Ethics for Governance of
Multi-Agent Systems (COINE), co-located with AAMAS 202