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We present a modular evolutionary framework, coined CASE for "complex adaptive system evolver", to automate the modeling and analysis of agent-based simulations (ABSs). The field of agent-based modeling is rapidly growing due to its capabilities to expose the emerging complex phenomena occurring in a wide range of natural and artificial systems such as biological cells, societies, battlefields,...
Evolving agent-based simulations enables one to automate the difficult iterative process of modeling complex adaptive systems to exhibit pre-specified/desired behaviors. Nevertheless this emerging technology, combining research advances in agent-based modeling/simulation and evolutionary computation, requires significant computing resources (i.e., high performance computing facilities) to evaluate...
Simulating crowds is a challenging but important problem. There are various methodologies in the literature ranging from macroscopic numerical flow simulations to detailed, microscopic agent simulations. One key issue for all crowd simulations is scalability. Some methods address this issue through abstraction, describing global properties of homogeneous crowds. However, ideally a modeler should be...
Symbiotic simulation is a paradigm in which a simulation system and a physical system are closely associated with each other. This close relationship can be mutually beneficial. The simulation system benefits from real-time measurements about the physical system which are provided by corresponding sensors. The physical system, on the other side, may benefit from the effects of decisions made by the...
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