This Repast Simphony model simulates genomic admixture during the farming expansion of human groups from mainland Asia into the Papuan dominated islands of Southeast Asia during the Neolithic period.

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 Opportunistic Acquisition Model (OAM) posits that the archaeological lithic raw material frequencies are due to opportunistic encounters with sources while randomly walking in an environment.

The model proposes a translation of some Luhmann’s concepts (social sub-system, perturbation, dissipation, social communication and power) into a model using a stylized spatial-society as a metaphor of a Luhmann’s social subsystem. The model has been used to improve the social theory understanding and to evaluate the effect of different parameterization in the global stabilization and individual/social power distribution.

This model is represents an effort to replicate one of the first attempts (van der Vaart 2006) to develop an agent based model of agricultural origins using principles and equations drawn from human behavioral ecology. We have taken one theory of habitat choice (Ideal Free Distribution) and applied it to human behavioral adaptations to differences in resource quality of different habitats.

This model allows for analyzing the most efficient levers for enhancing the use of recycled construction materials, and the role of empirically based decision parameters.

This model simulates the interactions and dynamic trust changes between people which results in social group emergence and evolution.

This is a model of coherency based belief within a dynamic network of individuals. Described in an invited talk on workshop on Coherence, Berlin, 9th July 2016.

This is code repository for the paper “Homophily as a process generating social networks: insights from Social Distance Attachment model”.
It provides all information, code and data necessary to replicate all the simulations and analyses presented in the paper.
This document contains the overall instruction as well as description of the content of the repository.
Details regarding particular stages are documented within source files as comments.

We introduce a model of prediction markets that uses opinion dynamics as its underlying mechanism for price formation. We base the opinion dynamics on the Deffuant model of bounded rationality. We have used this model to show that price formation in prediction markets can be robustly explained by opinion dynamics, and that the model can also explain phase transitions depending on just two parameters.