  This paper presents a modular approach to discover process models for
multi-agent systems from event logs. System event logs are filtered according
to individual agent behavior. We discover workflow nets for each agent using
existing process discovery algorithms. We consider asynchronous interactions
among agents. Given a specification of an interaction protocol, we propose a
general scheme of workflow net composition. By using morphisms, we prove that
this composition preserves soundness of components. A quality evaluation shows
the increase in the precision of models discovered by the proposed approach.
