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.

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

Aroused public opinion has led to public debates on social responsibility issues in food supply chains. This model based op opinion dynamics and the linkages between involved actors simulates the public debate leading to the transitions.

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.

This version of the accumulated copying error (ACE) model is designed to address the following research question: how does finite population size (N) affect the coefficient of variation (CV) of a continuous cultural trait under the assumptions that the only source of copying error is visual perception error and that the continuous trait can take any positive value (i.e., it has no upper bound)? The model allows one to address this question while assuming the continuous trait is transmitted via vertical transmission, unbiased transmission, prestige biased transmission, mean conformist transmission, or median conformist transmission. By varying the parameter, p, one can also investigate the effect of population size under a mix of vertical and non-vertical transmission, whereby on average (1-p)N individuals learn via vertical transmission and pN individuals learn via either unbiased transmission, prestige biased transmission, mean conformist transmission, or median conformist transmission.

The SMASH model is an agent-based model of rural smallholder households. It models households’ evolving income and wealth, which they earn through crop sales. Wealth is carried in the form of livestock, which are grazed on an external rangeland (exogenous) and can be bought/sold as investment/coping mechanisms. The model includes a stylized representation of soil nutrient dynamics, modeling the inflows and outflows of organic and inorganic nitrogen from each household’s field.

The model has been applied to assess the resilience-enhancing effects of two different farm-level adaptation strategies: legume cover cropping and crop insurance. These two strategies interact with the model through different mechanims - legume cover cropping through ecological mechanisms and crop insurance through financial mechanisms. The model can be used to investigate the short- and long-term effects of these strategies, as well as how they may differently benefit different types of household.

In the “World of Cows”, dairy farmers run their farms and interact with each other, the surrounding agricultural landscape, and the economic and political framework. The model serves as an exemplary case of an interdependent human-environment system.

With the model, users can analyze the influence of policies and markets on land use decisions of dairy farms. The land use decisions taken by farms determine the delivered ecosystem services on the landscape level. Users can choose a combination of five policy options and how strongly market prices fluctuate. Ideally, the choice of policy options fulfills the following three “political goals” 1) dairy farming stays economically viable, 2) the provision of ecosystem services is secured, and 3) government spending on subsidies is as low as possible.

The model has been designed for students to practice agent-based modeling and analyze the impacts of land use policies.

This is a preliminary attempt in creating an Agent-Based Model of capital flows. This is based on the theory of capital flows based on interest-rate differentials. Foreign capital flows to a country with higher interest rates relative to another. The model shows how capital volatilty and wealth concentration are affected by the speed of capital flow, number of investors, magnitude of changes in interest rate due to capital flows and the interest differential threshold that investors set in deciding whether to move capital or not. Investors in the model are either “regional” investors (only investing in neighboring countries) and “global” investors (those who invest anywhere in the world).

In the future, the author hopes to extend this model to incorporate capital flow based on changes in macroeconomic fundamentals, exchange rate volatility, behavioral finance (for instance, herding behavior) and the presence of capital controls.

This generic individual-based model of a bird colony shows how the influence neighbour’s stress levels synchronize the laying date of neighbours and also of large colonies. The model has been used to demonstrate how this form of simulation model can be recognised as being ‘event-driven’, retaining a history in the patterns produced via simulated events and interactions.

This model aims to simulate Competition and Displacement of Online Interpersonal Communication Platforms process from a bottom-up angle. Individual interpersonal communication platform adoption and abandonment serve as the micro-foundation of the simulation model. The evolution mode of platform user online communication network determines how present platform users adjust their communication relationships as well as how new users join that network. This evolution mode together with innovations proposed by individual interpersonal communication platforms would also have impacts on the platform competition and displacement process and result by influencing individual platform adoption and abandonment behaviors. Three scenes were designed to simulate some common competition situations occurred in the past and current time, that two homogeneous interpersonal communication platforms competed with each other when this kind of platforms first came into the public eye, that a late entrant platform with a major innovation competed with the leading incumbent platform during the following days, as well as that both the leading incumbent and the late entrant continued to propose many small innovations to compete in recent days, respectively.
Initial parameters are as follows: n(Nmax in the paper), denotes the final node number of the online communication network node. mi (m in the paper), denotes the initial degree of those initial network nodes and new added nodes. pc(Pc in the paper), denotes the proportion of links to be removed and added in each epoch. pst(Pv in the paper), denotes the proportion of nodes with a viscosity to some platforms. comeintime(Ti in the paper), denotes the epoch when Platform 2 joins the market. pit(Pi in the paper), denotes the proportion of nodes adopting Platform 2 immediately at epoch comeintime(Ti). ct(Ct in the paper), denotes the Innovation Effective Period length. In Scene 2, There is only one major platform proposed by Platform 2, and ct describes that length. However, in Scene 3, Platform 2 and 1 will propose innovations alternately. And so, we set ct=10000 in simulation program, and every jtt epochs, we alter the innovation proposer from one platform to the other. Hence in this scene, jtt actually denotes the Innovation Effective Period length instead of ct.