The aim of our model is to investigate the team dynamics through two types of task allocation strategies, with a focus on the dynamic interplay between individual needs and group performance. To achieve this goal, we have formulated an agent-based model (ABM) to formalize Deci & Ryan’s self-determination theory (SDT) and explore the social dynamics that govern the relationship between individual and group levels of team performance.

Industrial clustering patterns are the result of an entrepreneurial process where spinoffs inherit the ideas and attributes of their parent firms. This computational model maps these patterns using abstract methodologies.

This model simulates movements of mobile pastoralists and their impacts on the transmission of foot-and-mouth disease (FMD) in the Far North Region of Cameroon.

Overview

The Weather model is a procedural generation model designed to create realistic daily weather data for socioecological simulations. It generates synthetic weather time series for solar radiation, temperature, and precipitation using algorithms based on sinusoidal and double logistic functions. The model incorporates stochastic variation to mimic unpredictable weather patterns and aims to provide realistic yet flexible weather inputs for exploring diverse climate scenarios.

The Weather model can be used independently or integrated into larger models, providing realistic weather patterns without extensive coding or data collection. It can be customized to meet specific requirements, enabling users to gain a better understanding of the underlying mechanisms and have greater confidence in their applications.

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This is a variant of the PaleoscapeABM model available here written by Wren and Janssen. In this variant, we give projectile weapons to hunter and document where they discard them over time. Discard rate and location are influenced by probabilities of hitting/missing the prey, probabilities of damaging the weapon, and probabilities of carrying back embedded projectile armatures to the habitation camp with the body carcass.

This is an opinion dynamics model which extends the model found in (Martins 2009). The previous model had an unshared uncertainty assumption in agent-to-agent interaction this model relaxes that assumption. The model only supports a fully connect network where every agent has an equal likelihood of interacting with every other agent at any given time step. The model is highly modular so different social network paradigm can easier be implemented.

The model measures drivers of effectiveness of risk assessments in risk workshops regarding the correctness and required time. Specifically, we model the limits to information transfer, incomplete discussions, group characteristics, and interaction patterns and investigate their effect on risk assessment in risk workshops.

The model simulates a discussion in the context of a risk workshop with 9 participants. The participants use Bayesian networks to assess a given risk individually and as a group.

BarterNet is a platform for modeling early barter networks with the aim of learning how supply and demand for a good determine if traders will learn to use that good as a form of money. Traders use a good as money when they offer to trade for it even if they can’t consume it, but believe that they can subsequently trade it for a good they can consume in the near future.

CHALMS simulates housing and land market interactions between housing consumers, developers, and farmers in a growing ex-urban area.

This model simulates different spread hypotheses proposed for the introduction of agriculture on the Iberian peninsula. We include three dispersal types: neighborhood, leapfrog, and ideal despotic distribution (IDD).