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Reasoning about concurrent stochastic systems

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Complex networks are often modelled as stochastic processes, to encapsulate a lack of knowledge or inherent non-determinism. Such systems are frequently modular in nature, consisting of parts which are systems in their own right. Their global behaviour depends on the behaviours of their parts and on the topology of the network. This talk focuses on identifying the mathematical structure of these systems and investigates the possibility to define a general (qualitative and quantitative) logical framework appropriate for modular analysis. By modular analysis we mean a scale-up approach that proves properties of an upper level system from the properties of its subsystems. On this direction, it is also possible to define distances between stochastic processes which measure their behavioural or structural similarities.

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