Within the archeological record for Bronze Age Chinese culture, there continues to be a gap in our understanding of the sudden rise of the Erlitou State from the previous late Longshan chiefdoms. In order to examine this period, I developed and used an agent-based model (ABM) to explore possible socio-politically relevant hypotheses for the gap between the demise of the late Longshan cultures and rise of the first state level society in East Asia. I tested land use strategy making and collective action in response to drought and flooding scenarios, the two plausible environmental hazards at that time. The model results show cases of emergent behavior where an increase in social complexity could have been experienced if a catastrophic event occurred while the population was sufficiently prepared for a different catastrophe, suggesting a plausible lead for future research into determining the life of the time period.

The ABM published here was originally developed in 2016 and its results published in the Proceedings of the 2017 Winter Simulation Conference.

The purpose of this model is to analyze the dynamics of endogenously created oscillations in housing prices using a system dynamics simulation model, built from the perspective of construction companies.

CPNorm is a model of a community of harvesters using a common pool resource where adhering to the optimal extraction level has become a social norm. The model can be used to explore the robustness of norm-driven cooperation in the commons.

This ABM simulates opinions on a topic (originally contested infrastructures) through the interactions between paired agents and based on the sociopsychological assumptions of social judgment theory (SJT; Sherif & Hovland, 1961).

The aim of the model is to define when researcher’s assumptions of dependence or independence of cases in multiple case study research affect the results — hence, the understanding of these cases.

The model represents urban commuters’ transport mode choices among cars, public transit, and motorcycles—a mode highly prevalent in developing countries. Using an agent-based modeling approach, it simulates transport dynamics and serves as a testbed for evaluating policies aimed at improving mobility.

The model simulates an ecosystem of human agents who decide, at each time step, which mode of transportation to use for commuting to work. Their decision is based on a combination of personal satisfaction with their most recent journey—evaluated across a vector of individual needs—the information they crowdsource from their social network, and their personal uncertainty regarding trying new transport options.

Agents are assigned demographic attributes such as sex, age, and income level, and are distributed across city neighborhoods according to their socioeconomic status. To represent social influence in decision-making, agents are connected via a scale-free social network topology, where connections are more likely among agents within the same socioeconomic group, reflecting the tendency of individuals to form social ties with similar others.

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This is the code for the model described in an article in the International Journal of Microsimulation. Lawson (2013) ‘Modelling Household Spending Using a Random Assignment Scheme’, International Journal of Microsimulation, 6(2) Autumn 2013, 56-75.

We model interpersonal dynamics and study behavior in the classroom in the hypothetical case of a single teacher who defines students’ seating arrangements. The model incorporates the mechanisms of peer influence on study behavior, on attitude formation, and homophilous selection in order to depict the interrelated dynamics of networks, behavior, and attitudes. We compare various seating arrangement scenarios and observe how GPA distribution and level of prejudice changes over time.

This model computes the guaranteed viability kernel of a model describing the evolution of a population submitted to successive floods.
The population is described by its wealth and its adaptation rate to floods, the control are information campaigns that have a cost but increase the adaptation rate and the expected successive floods belong to given set defined by the maximal high and the minimal time between two floods.

The Mobility Transition Model (MoTMo) is a large scale agent-based model to simulate the private mobility demand in Germany until 2035. Here, we publish a very much reduced version of this model (R-MoTMo) which is designed to demonstrate the basic modelling ideas; the aim is by abstracting from the (empirical, technological, geographical, etc.) details to examine the feed-backs of individual decisions on the socio-technical system.