Titlebook: Cells and Robots; Modeling and Control Dejan Lj. Milutinovi?,Pedro U. Lima Book 2007 Springer-Verlag Berlin Heidelberg 2007 Multi-agent sys

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Micro-Agent and Stochastic Micro-Agent Models,d. This population model includes the full population complexity. Approximating this complexity by stochastic modeling leads to a .. Biologically motivated Micro-Agent and Stochastic Micro-Agent are formally defined in Section 3.4 and Section 3.5, respectively.

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1610-7438 ered and their behaviour controlled.Prize winner in the 5th .Cells and Robots. is an outcome of the multidisciplinary research extending over Biology, Robotics and Hybrid Systems Theory. It is inspired by modeling reactive behavior of the immune system cell population, where each cell is considered

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https://doi.org/10.1007/978-3-319-75145-0. The main motivation of our approach is to provide fundamental principles of modeling and control for large-size populations, providing math-based tools for the analysis and control design from specifications.

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Book 2007ing reactive behavior of the immune system cell population, where each cell is considered as an independent agent. In our modeling approach, there is no difference if the cells are naturally or artificially created agents, such as robots. This appears even more evident when we introduce a case study

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Micro-Agent Population Dynamics, of individual particles. A straightforward application of this theory to a general Micro-Agent population is not possible. However, it provides us with an insight on how to make a bridge between the micro-dynamics of the individual Micro-Agent and the Micro-Agent population macro-dynamics.

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