Linked lives simulation models in demography comprise numerous agents, interacting in various roles in continuous time, with detailed decision processes, and dynamically accessing information in a social network that is evolving over time. These models are built partly based on established theories, other simulation models, and data, and evolve over time. From this observation diverse challenges for modeling and simulation do arise. An expressive modeling language is required that allows a succinct continuous-time modeling of linked lives models. The developed modeling language ML3 (Modeling Language for Linked Lives) shall be evaluated and refined in further case studies and in the context of other modeling languages. An efficient execution is a prerequisite for a thorough development and analysis of such models. Therefore, parallel and approximate simulators shall be developed. For effectively applying parallel simulation to linked lives models, suitable strategies for partitioning the social network are necessary, whereas the effectiveness of approximate simulators in successfully balancing accuracy and speed relies on suitable aggregation strategies. Both types of strategies will be subject of research. To support flexible and replicable simulation experiments, a binding between ML3 and SESSL (Simulation Experiment Specification via a Scala Layer) was developed. Methods to analyze dynamic networks shall add to the portfolio of analysis methods already provided. The declarative description of models in ML3 and of simulation experiments in SESSL shall form the basis to automatically derive provenance information about the various artifacts and processes that contributed to linked lives models. The developed methods will be evaluated based on concrete simulation studies in demography.
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