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We consider dynamics represented by successive stochastic moves. Assuming we know the transition probabilities for going from one configuration to the next, we will discuss ways to determine the probabilities of the individual configurations.
We point out that complexity science is developing fast and that present and future scientific and societal challenges will need fundamental improvements in our ability to analyse and deal with complex emergent behaviour. It is therefore desirable to spread widely the awareness of approaches and insights from complexity science.
Conceptual and mathematical models can serve many purposes. We will discuss why simple stylistic models are particularly useful in complexity science since they can help to identify the most essential mechanisms amongst the profusion of interdependencies at play.
When interactions between individual dynamical components are sufficiently strong, coordinated dynamics at the systemic level can emerge. This is called synchronisation.
We present a few paradigmatic modelling strategies selected due to their generality in addressing the emergence of spatio-temporal structure, including criticality, synchronisation, intermittency, adaptation and forecasting.
The chapters of Part I will discuss why complexity science is important, how this science relates to other sciences and also a little bit about its philosophical status. The aim is to make clear what makes complexity science special and in which way it contributes to our understanding of the surrounding world.
Many types of emergence exist. This chapter will discuss some of the most prominent, and broadly occurring, examples of emergent structure in space and time.
The process of entities successively splitting into two or more is of great relevance: biological reproduction, infection spreading, rumour spreading, nuclear reactions and much more.