Communities of autonomous units are rule-based and graphtransformational systems with a well-defined formal semantics. The autonomous units of a community act and interact in a common environment while striving for their goals. Ant colony systems consist of a set of autonomously behaving ants and are often employed as a metaheuristics for NP-hard logistic problems. In this paper, we demonstrate how communities of autonomous units can be used as a formal graph-transformational framework for modeling ant colony systems. As a first example we model an ant colony system for the Traveling Salesperson Problem as a community of autonomous units.

Abstract. In this paper an heuristic method for the solving of complex optimization problems is presented which is inspired equally by genetic algorithms and graph transformation. In short it can be described as a genetic algorithm where the individuals (encoding solutions of the given problem) are always graphs and the operators to create new individuals are provided by graph transformation. As a case study this method is used to solve the independent set problem.