Invited Talk: Extensions of Graph Transformation Systems for Timed, Continuous, and Probabilistic Behavior

Abstract

Graph transformation systems can be employed to describe systems with
complex structural dynamics which states can be captured by attributed graphs.
However, like many other standard computer science models such as automata in
their basic form time, continuous behavior, or probabilistic behavior are not supported.
In this talk we will report on a number of extensions for graph transformation
systems that have been developed that permit to describe also time, continuous
behavior, probabilistic behavior, timed probabilistic behavior. Referring to the development
of related extensions for automata, we will discuss how these results
have been transferred to graph transformation systems. We will discuss furthermore
which specific problems had to be resolved to transfer the results to graph transformation
systems, which tool support exists, and what are the open challenges for
each of these directions