Abstract for: Structurally Evolving System Dynamics Models Using Genetic Algorithms

In this paper we discuss how to automatically generate system dynamics models using a kind of genetic algorithm known as a genetic program. This allows both the structure and the parameters of the system dynamics models under study to be evolved. This paper builds on previous work that introduced the use of genetic programs to automatically generate system dynamics models. The paper’s contribution is that it discusses how to automatically generate anticipatory system dynamics in weakly constrained, data-sparse domains. The paper also describes how this technique might be applied to an example domain, namely that of transnational organized crime. This paper reports the status of work in progress. At the time of submission, the designs described in this paper were partially, but not fully, implemented.