• Oliver Nakoinz
  • Daniel Knitter
Part of the Quantitative Archaeology and Archaeological Modelling book series (QAAM)


Simulations are usually seen as an advanced type of models. They are empirical models of artificial data generated according to theoretical rules, attempting to imitate real processes or structures by applying certain rules on random data or observations. The final model uses techniques to reconstruct empirical models with the input of the artificial data. The rather complex relationship between the empirical and theoretical components sometimes makes it difficult to interpret the results. Stochastic simulations like Monte Carlo simulations use random numbers of a certain distribution rather than real observations. Simulations of point processes bear great potential for archaeological problems, since they are direct comparable with archaeological sources. Grid-based simulations have many restrictions but are useful for studying certain phenomena. Agent-based modelling applies a set of behaviour rules to agents—entities capable of behaviour—in an iterative process, while multi-agent models allow the interaction of agents.


Simulation Random number Point process simulations Point based simulations Grid based simulations Cellular automata Agent based simulations 


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Oliver Nakoinz
    • 1
  • Daniel Knitter
    • 2
  1. 1.University of KielKielGermany
  2. 2.Excellence Cluster TopoiFreie UniversitätBerlinGermany

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