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

The code contains four experiments for well-being based IMRL reward features.

CEDSS is an agent-based model of domestic energy demand at the level of a small community.

The St Anthony flu model is an epidemiological model designed to test hypotheses related to the spread of the 1918 influenza pandemic among residents of a small fishing community in Newfoundland and Labrador. The 1921 census data from Newfoundland and Labrador are used to ensure a realistic model population; the community of St. Anthony, NL, located on the tip of the Northern Peninsula of the island of Newfoundland is the specific population modeled. Model agents are placed on a map-like grid that consists of houses, two churches, a school, an orphanage, a hospital, and several boats. They engage in daily activities that reflect known ethnographic patterns of behavior in St. Anthony and other similar communities. A pathogen is introduced into the community and then it spreads throughout the population as a consequence of individual agent movements and interactions.

This model is designed to address the following research question: How does the amount and topology of intergroup cultural transmission modulate the effect of local group extinction on selectively neutral cultural diversity in a geographically structured population? The experimental design varies group extinction rate, the amount of intergroup cultural transmission, and the topology of intergroup cultural transmission while measuring the effects of local group extinction on long-term cultural change and regional cultural differentiation in a constant-size, spatially structured population. The results show that for most of the intergroup social network topologies tested here, increasing the amount of intergroup cultural transmission (similar to increasing gene flow in a genetic model) erases the negative effect of local group extinction on selectively neutral cultural diversity. The stochastic (i.e., preference attachment) network seems to stand out as an exception.

The BASAR model aims to investigate different approaches to describe small-scale farmers’ decision-making in the context of diversified agroforestry adoption in rural Rwanda. Thereby, it compares random behaviour with perfect rationality (non-discounted and discounted utility maximization), bounded rationality (satisficing and fast and frugal decision tree heuristics), Theory of Planned Behaviour, and a probabilistic regression-based approach. It is aimed at policy-makers, extension agents, and cooperatives to better understand how rural farmers decide about implementing innovative agricultural practices such as agroforestry and at modelers to support them in selecting an approach to represent human decision-making in ABMs of Social-Ecological Systems. The overall objective is to identify a suitable approach to describe human decision-making and therefore improve forecasts of adoption rates and support the development and implementation of interventions that aim to raise low adoption rates.

This is a simulation model to explore possible outcomes of the Port of Mars cardgame. Port of Mars is a resource allocation game examining how people navigate conflicts between individual goals and common interests relative to shared resources. The game involves five players, each of whom must decide how much of their time and effort to invest in maintaining public infrastructure and renewing shared resources and how much to expend in pursuit of their individual goals. In the game, “Upkeep” is a number that represents the physical health of the community. This number begins at 100 and goes down by twenty-five points each round, representing resource consumption and wear and tear on infrastructure. If that number reaches zero, the community collapses and everyone dies.

The model is a stylized representation of a social-ecological system of agents moving and harvesting a renewable resource. The purpose is to analyze how mobility affects sustainability. Experiments changing agents’ mobility, landscape and information governments have can be run.

Food trade networks represent a complex system where food is periodically produced in different regions of the world. Food is continuously stocked and traded. Food security in a globalised world is vulnerable to shocks. We present DARTS, a new agent based model that models monthly dynamics of food production, trade, stocking, consumption and food security for different interconnected world regions and a city state. Agents in different regions differ in their harvest seasons, wealth (rich and poor), degree of urbanisation and connection to domestic and global markets. DARTS was specifically designed to model direct and indirect effects of shocks in the food system. We introduce a new typology of 6 distinct shock types and analyse their impact on food security, modelling local and global effects and short term and longer term effects. An second important scientific novelty of the model is that DARTS can also model indirect effects of shocks (cascading in space and in time, lag effects due to trade and food stock buffering). A third important scientific novelty of the model is its’ capability of modelling food security at different scales, in which the rural/urban divide and differences in (intra-annually varying) production and trade connections play a key role. At the time of writing DARTS is yet insufficiently parameterised for accurate prediction for real world regions and cities. Simulations for a hypothetical in silico world with 3 regions and a city state show that DARTS can reproduce rich and complex dynamics with analogues in the real world. The scientific interest is more on deepening insight in process dynamics and chains of events that lead to ultimate shock effects on food security.

This is a model of the occurrence of disorganization and its impact on individual goal setting and problem-solving. This model therefore, explores the effects of disorganization on goal achievement.