The Land Use Competition in Drylands (LUCID) model is a stylized agent-based model of a smallholder farming system. Its main purpose is to illustrate how competition between pastoralism and crop cultivation can affect livelihoods of households, specifically their food security. In particular, the model analyzes whether the expansion of crop cultivation may contribute to a vicious circle where an increase in cultivated area leads to higher grazing pressure on the remaining pastureland, which in turn may cause forage shortages and livestock loss for households which are then forced to further expand their cultivated area in order to increase their food security. The model does not attempt to replicate a particular case study but to generate a general understanding of mechanisms and drivers of such vicious circles and to identify possible scenarios under which such circles may be prevented.

The model is inspired by observations of the Borana land use system in Southern Ethiopia. The climatic and ecological conditions of the Borana zone favor pastoralism, and traditionally livelihoods have been based mainly on livestock keeping. Recent years, however, have seen an advancement of crop cultivation as a coping strategy, e.g., to compensate the loss of livestock, even though crop yields are low on average and successful harvests are infrequent.

In the model, it is possible to evaluate patterns of individual (single household) as well as overall (across all households) consumption and food security, depending on a range of ecological, climatic and management parameters.

An agent-based model simulates emergence of in-group favoritism. Agents adopt friend selection strategies using an invariable tag and reputations meaning how cooperative others are to a group. The reputation can be seen as a kind of public opinion.

We present an agent-based model that maps out and simulates the processes by which individuals within ecological restoration organizations communicate and collectively make restoration decisions.

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

In our model, individual agents are distributed over a two-dimensional square lattice. The agents play the prisoner’s dilemma game with their neighbors, imitate the highest strategy, and then migrate to empty sites based on their tag preference.

RaMDry allows to study the dynamic use of forage ressources by herbivores in semi-arid savanna with an emphasis on effects of change of climate and management. Seasonal dynamics affects the amount and the nutritional values of the available forage.

We develop an IBM that predicts how interactions between elephants, poachers, and law enforcement affect poaching levels within a virtual protected area. The model is theoretical at this stage and is not meant to provide a realistic depiction of poaching, but instead to demonstrate how IBMs can expand upon the existing modelling work done in this field, and to provide a framework for future research. The model could be further developed into a useful management support tool to predict the outcomes of various poaching mitigation strategies at real-world locations. The model was implemented in NetLogo version 6.1.0.

We first compared a scenario in which poachers have prescribed, non-adaptive decision-making and move randomly across the landscape, to one in which poachers adaptively respond to their memories of elephant locations and where other poachers have been caught by law enforcement. We then compare a situation in which ranger effort is distributed unevenly across the protected area to one in which rangers patrol by adaptively following elephant matriarchal herds.

Leptospirosis is a neglected, bacterial zoonosis with worldwide distribution, primarily a disease of poverty. More than 200 pathogenic serovars of Leptospira bacteria exist, and a variety of species may act as reservoirs for these serovars. Human infection is the result of direct or indirect contact with Leptospira bacteria in the urine of infected animal hosts, primarily livestock, dogs, and rodents. There is increasing evidence that dogs and dog-adapted serovar Canicola play an important role in the burden of leptospirosis in humans in marginalized urban communities. What is needed is a more thorough understanding of the transmission dynamics of Leptospira in these marginalized urban communities, specifically the relative importance of dogs and rodents in the transmission of Leptospira to humans. This understanding will be vital for identifying meaningful intervention strategies.
One of the main objectives of MHMSLeptoDy is to elucidate transmission dynamics of host-adapted Leptospira strains in multi-host system. The model can also be used to evaluate alternate interventions aimed at reducing human infection risk in small-scale communities like urban slums.

This ABM looks at the effect of multiple reviewers and their behavior on the quality and efficiency of peer review. It models a community of scientists who alternatively act as “author” or “reviewer” at each turn.

Negotiation Lab 1.0 is an agent-based model of peace negotiations that explores how the parties’ readiness — their motivation and optimism to engage in talks — evolves dynamically throughout the negotiation process. The model reconceptualizes readiness as an adaptive state variable that is continuously updated through feedback from negotiation outcomes, rather than a static precondition assessed at the onset of talks.
The model simulates two parties negotiating a multi-issue agenda. In each round, parties allocate effort to the current sub-issue; outcomes depend on their joint effort and a stochastic component representing external factors. Results feed back into each party’s readiness, shaping subsequent engagement. The negotiation ends either when all agenda items are resolved (agreement) or when a party’s readiness falls below a critical threshold (breakdown).
Key parameters include the initial readiness of each party, agenda structure (balanced, hard, easy, red, or random), type of negotiation (from highly cooperative to highly competitive), and each party’s effort strategy (always high, always low, random, or pseudo tit-for-tat). The model shows that while initial readiness is associated with negotiation outcomes, it is neither necessary nor sufficient to determine them: process variables — the type of interaction, agenda design, and adaptive effort strategies — exert comparatively larger effects on outcomes. Identical initial conditions can produce widely divergent trajectories, illustrating path dependence and sensitivity to feedback dynamics.
The model is implemented in NetLogo 7.0 and is documented using the ODD+D protocol. It is associated with the paper “Beyond Initial Conditions: How Adaptive Readiness Shapes Peace Negotiation Outcomes” (Arévalo, under review).