Individuation and Adaptation in Complex Systems
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Complex systems have certain characteristics such as network structures of a large number of individual elements, adaptation, and emergence. While these characteristics have been studied and described, it is often not so clear where they exactly come from. There is a focus on concrete system states rather than the emergence of the computer models themselves used to study these systems. To better understand typical characteristics of complex systems and their emergence, we recently presented a system metamodel based on which computer models can be created from abstract building blocks. In this study we extend our system metamodel with the concept of adaption in order to integrate adaptive computation in our so-called allagmatic method - a framework consisting of the system metamodel but also a way to study the creation of the computer model itself. Running experiments with cellular automata and artificial neural networks, we find that the system metamodel integrates adaptation with an additional operation called adaptation function that operates on the update function, which encodes the system's dynamics. It allows the creation of adaptive computations by providing an abstract template for adaptation and guidance for implementation. Further, the object-oriented and template meta-programming leads to a creation of computer models comparable to the individuation of observed systems. It therefore allows to study not only the behaviour of a running model but also its creation. The development of the system metamodel was first inspired by concepts of the philosophy of individuation of Gilbert Simondon. The theoretical background for the concept of adaptation is taken from the philosophy of organism of Alfred North Whitehead. In general, through the possibility to follow individuation, the allagmatic method allows to better understand the emergence of typical characteristics of complex systems.
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