Designing complex, self-organising systems is challenging. It requires to find local, decentralised rules for the agents which result in a good global performance of the overall system. In this talk, two approaches are presented at the example of a self-organising manufacturing system where local dispatching rules are used for decentralised scheduling.

The first approach supports a human designer by revealing the weaknesses of an examined manufacturing system. This is achieved by automatically searching for easy-to-analyse problem instances where the applied dispatching rule performs poorly.
The other approach is to generate the dispatching rules automatically by simulation-based Genetic Programming.