Multi-agent causal models for dependability analysis
Sam Maes and Philippe Leray
In: First International Conference on Availability, Reliability and Security (ARES 2006), Bayesian Networks in Dependability (BND 2006) workshop, 20-22 April 2006, Vienna, Austria.
In this paper we discuss multi-agent causal models,
which are an extension of causal Bayesian networks to the
multi-agent case. In this paper we illustrate how these re-
cently introduced models could prove useful for dependabil-
ity analysis. Their main difference with other graphical
modeling techniques that have been applied to the prob-
lem is that multi-agent causal models allow for multi-agent,
privacy-preserving quantitative causal inference in models
with hidden variables.