The model examines cattle herd dynamics on a patchy grassland subject to two exogenous pressures: periodic raiding events that remove animals and scheduled management culling that can target males and/or females. It is intended for comparative experiments on how raiding frequency, culling schedules, vegetation dynamics, and life-history parameters interact to shape herd persistence. The model was specifically designed to test the scenario of cattle herding in the arid grasslands of southern Arizona and northern Sonora during the mission period (late 17th through late 18th centuries, CE). In this period, herds were locally managed by Spanish mission personnel and local O’odham groups. Herds were culled mostly for local consumption of meat, hides, and tallow, but the mission herds were often targets for raiding by neighboring groups. The main purpose of the model is to examine herd dynamics in a seasonally variable, arid environment where herds are subject to both intentional internal harvest (culling) and external harvest (raiding).

Although beneficial to scientific development, data sharing is still uncommon in many research areas. Various organisations, including funding agencies that endorse open science, aim to increase its uptake. However, estimating the large-scale implications of different policy interventions on data sharing by funding agencies, especially in the context of intense competition among academics, is difficult empirically. Here, we built an agent-based model to simulate the effect of different funding schemes (i.e., highly competitive large grants vs. distributive small grants), and varying intensity of incentives for data sharing on the uptake of data sharing by academic teams strategically adapting to the context.

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.

We build a stylized model of a network of business angel investors and start-up entrepreneurs. Decisions are based on trust as a decision making tool under true uncertainty.

Implemented as a virtual laboratory, this model explores transitions in land-use and livelihood decisions that emerge from changing local and global conditions.

We represent commuters and their preferences for transportation cost, time and safety. Agents assess their options via their preferences, their environment, and the modes available. The model has policy levers to test impact on last-mile problem.

This is a social trust model for investigating the social relationships and social networks in the real world and in social media.

We demonstrate how Repast Simphony statecharts can efficiently encapsulate the deep classification hierarchy of the U.S. Air Force for manpower life cycle costing.

Agent-based version of the simple search and barter economy conceived by Peter Diamond in 1982. The model is also known as Coconut Model.

An artifcal stock market model that allows users to vary the number of risky assets as well as the network topology that investors forms in an attempt to understand the dynamics of the market.