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The domain-specific modeling and simulation language ML-Rules is aimed at facilitating the description of cell biological systems at different levels of organization. Model states are chemical solutions that consist of dynamically nested, attributed entities. The model dynamics are described by rules that are constrained by arbitrary functions, which can(More)
The domain specific modeling and simulation language ML-Rules makes it possible to describe cell biological systems at different levels of organization. A model is formed by attributed and dynamically nested species, with reactions that are constrained by functions on attributes. In this paper, we extend ML-Rules to also support constraints using functions(More)
Agent-based modeling and simulation is widely used in computational demography. Although existing agent-based approaches allow modeling linked lives in a rather flexible manner, the resulting models, due to typically being implemented in a general-purpose programming language, often lack the compactness required to easily access the model. With ML3(More)
Currently, only few agent-based models are implemented with a continuous representation of time, although state-of-the-art agent-based modeling and simulation (ABMS) frameworks support continuous-time models and continuous time often allows for a more faithful capturing of reality. Intrigued by this discrepancy, we take a closer look at population-based(More)
  • Tom Warnke
  • 2016
Most state-of-the-art agent-based modeling and simulation (ABMS) frameworks offer a way to describe agent behavior in a programming language. Whereas these frameworks support easy development of time-stepped models, continuous-time models can only be implemented by manually scheduling and retracting events as part of the agent behavior. To facilitate a(More)
The complexity and size of simulation models is steadily increasing. As a consequence, input and output of simulations increase in complexity as well. This is particularly true for spatial, multi-level models where different structures might be of interest [1]. Therefore, new methods are required that support the experimentation process with these models.(More)
For models that include spatial aspects, the description and recognition of spatio-temporal patterns is an important building block for the analysis of simulation trajectories. We propose an approach that makes use of user-definable qualitative spatial relations between moving entities to represent simulation trajectories as directed labeled graph. In this(More)
Model development is a successive process of validating, revising, and extending models, and requires iterative execution of simulation experiments. While developing a model by extension, executing similar simulation experiments to those performed with the original model reveals important behavioral insights into the extended model. An automatic generation(More)
A dramatic increase in malnourished cod can presently be observed in the Eastern Baltic. Simulation studies help unraveling possible reasons behind this. Particularly, individual-based modeling approaches are promising as they facilitate taking into account the heterogeneity of the cod population, where size, temperature etc. determine behavior patterns.(More)
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