This model examines language dynamics within a social network using simulation techniques to represent the interplay of language adoption, social influence, economic incentives, and language policies. The agent-based model (ABM) focuses on interactions between agents endowed with specific linguistic attributes, who engage in communication based on predefined rules. A key feature of our model is the incorporation of network analysis, structuring agent relationships as a dynamic network and leveraging network metrics to capture the evolving inter-agent connections over time. This integrative approach provides nuanced insights into emergent behaviors and system dynamics, offering an analytical framework that extends beyond traditional modeling approaches. By combining agent-based modeling with network analysis, the model sheds light on the underlying mechanisms governing complex language systems and can be effectively paired with sociolinguistic observational data.

CROwd Simulation of Situated individuals represents a modern generation simulation as a (social) scientific tool for understanding crowd behaviour. The CROSS model represents individuals in a crowd as social-cognitive agents that are affected by their social and physical surroundings and produce behaviour and behaviour patterns.

The simulation model SimPLS shows an application of the PLS agent concept, using SEM as empirical basis for the definition of agent architectures. The simulation model implements the PLS path model TAM about the decision of using innovative products.

This model simulates a foraging system based on Middle Stone Age plant and shellfish foraging in South Africa.

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 model simulates the spatial patterns of secondary forest succession above the current alpine tree line in the context of land use and climate change. Three scenarios are offered: (1) climate change, (2) land use change, (3) species composition.

The purpose of this model is to explore the impact of combining archaeological palimpsests with different methods of cultural transmission on the visibility of prehistoric social networks. Up until recently, Paleolithic archaeologists have relied on stylistic similarities of artifacts to reconstruct social networks. However, this method - which is successfully applied to more recent ceramic assemblages - may not be applicable to Paleolithic assemblages, as several of those consist of palimpsests of occupations. Therefore, this model was created to study how palimpsests of occupation affect our social network reconstructions.

The model simplifies inter-groups interactions between populations who share cultural traits as they produce artifacts. It creates a proxy archaeological record of artifacts with stylistic traits that can then be used to reconstruct interactions. One can thus use this model to compare the networks reconstructed through stylistic similarities with direct contact.

The publication and mathematical model upon which this ABM is based shows one mechanism that can lead to stable behavioral and cultural traits between groups.

This model (CharRec) creates simulated charcoal records, based on differing natural and anthropogenic patterns of ignitions, charcoal dispersion, and deposition.

We build a computational model to investigate, in an evolutionary setting, a series of questions pertaining to happiness.