Session 23 - Modelling approaches to investigate population dynamics and settlement patterns over the long term
Exploring the complexity – system dynamics and agent-based population model of the late Iron Age settlement agglomerations
On a transition from middle to late Iron Age period we encounter a transformation of the central European society which was represented especially by the new settlement forms – the oppida. They appeared as a part of an economically advanced environment, together with a distinctive intensification of settlement patterns. When they emerged, being understood as “deliberate foundations rather than a gradual evolution”, they represented complex systems with multiple functions. The central European sites share many characteristics, among them a distinct development of the population density: archaeological record shows that dynamics of the oppida occupation includes fast growth followed by even more rapid decline. Causes for gradual trend of depopulation can be seen in both endogenous and exogenous factors. However, their analysis is obstructed by the overall lack of detailed archaeological data. In this situation building of explanatory models is the only valid way of exploring the complexity of past societies.
Our objective is to explore the complexity of the population development at the end of the Iron Age using the combination of system dynamics and agent-based population dynamics model. System dynamics models provide an invaluable way to explore and test various general theoretical hypotheses related to the functioning of the settlements or the societal rules that are shaping them. Agent-based approach enables enhancing models with individuals having variety of behavioural patterns. The models are based on domain knowledge and general palaeodemographic patterns of birth-rates, mortality and migration. The simulation of synthetic population (size, structure and subsistence needs) is accompanied by the model of agricultural practices with the aim of investigating the sustainability of the long-term means of production and means of subsistence. The model was implemented in NetLogo and its System Dynamics Modeler. Results obtained with the simulation demonstrate limits of the sustainable economy practiced by a constantly growing population under particular environmental and societal settings. The immediate or gradual impact of the success rate in the food production and its potential influences on the economic and social processes including the oppida abandonment are also addressed.
Session 25 - Agents, Networks, Equations and Complexity: the potential and challenges of complex systems simulation
Agent based modelling and system dynamics – the importance of replicating models of past economies
Our research attempts to discuss the applicability of agent-based social simulation as a tool for exploration the late Iron Age society, especially from the point of view of the population growth and related sustainability of production. We intend to demonstrate the ability to move from a static data set (archaeological and environmental records) to dynamic modelling that incorporates feedback mechanisms, system integration, and nonlinear responses to a wide range of input data. This approach can help to analyse past socio-economic processes, determine possible crisis factors and understand ecological and cultural changes.
The main objective of this contribution is to stress out the importance and benefits of replication of simulation models. Knowledge of how to replicate is not widespread within the social simulation community and is not included in agent-based modelling methodologies. But it is the replication of computational models what confirms that the experiments did not dependent on any local conditions and that the description of the model is complete. Moreover the replication is important for model verification, optimization and validation and it can foster shared understanding about modelling decisions. The replicated model can differ across at least six dimensions (time, hardware, languages, toolkits, algorithms and authors).
We present a case study of our own attempt to re-implement the model of the population dynamics and carrying capacity of the late Iron Age oppida in Bohemia. The model consists of two part (1) the system dynamics component is used to provide a way to explore and test various general theoretical hypotheses related to the functioning of the settlements and the societal rules that are shaping them, (2) the agent-based component enables enhancing the model with individuals having variety of behavioural patterns. The original model was created in NetLogo and tested using BehaviorSpace utility. The replication was designed by same authors using different Java-based toolkit - AnyLogic, the more complex multi-method simulation software.
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