PSoup is an educational program in which evolution is demonstrated, on the desk-top, as you watch. Blind bugs evolve sophisticated heuristic search algorithms to be the best at finding food fast.

This model simulates networking mechanisms of an empirical social network. It correlates event determinants with place-based geography and social capital production.

This is an empirical model described in http://dx.doi.org/10.1016/j.landurbplan.2010.05.001. The objective of the model is to simulate how the decision-making of farmers/agents with different strategies can affect the landscape structure in a region in the Netherlands.

Purpose of the model is to perform a “virtual experiment” to test the predator satiation hypothesis, advanced in literature to explain the mast seeding phenomenon.

MayaSim is an agent-based, cellular automata and network model of the ancient Maya. Biophysical and anthropogenic processes interact to grow a complex social ecological system.

This model simulates the emergence of a dual market structure from firm-level interaction. Firms are profit-seeking, and demand is represented by a unimodal distribution of consumers along a set of taste positions.

This model employs optimal foraging theory principles to generate predictions of which coastal habitats are exploited in climatically stable versus variable environments, using the American Samoa as a study area.

Using webs of replicas of Atwood’s Machine, we explore implications of the Maximum Power Principle. This is one of a series of models exploring the dynamics of sustainable economics – PSoup, ModEco, EiLab, OamLab, MppLab, TpLab, CmLab.

Using chains of replicas of Atwood’s Machine, this model explores implications of the Maximum Power Principle. It is one of a series of models exploring the dynamics of sustainable economics – PSoup, ModEco, EiLab, OamLab, MppLab, TpLab, EiLab.

We compare the effect of four activation regimes by measuring the appropriate opinion clustering statistics and also the number of emergent extremists.