The simulation experiment is for studying the influence of external supervision services on combating corruption.
Algorithm: evolutionary game theory

Grasslands have a large share of the world’s land cover and their sustainable management is important for the protection and provisioning of grassland ecosystem services. The question of how to manage grassland sustainably is becoming increasingly important, especially in view of climate change, which on the one hand extends the vegetation period (and thus potentially allows use intensification) and on the other hand causes yield losses due to droughts. Fertilization plays an important role in grassland management and decisions are usually made at farm level. Data on fertilizer application rates are crucial for an accurate assessment of the effects of grassland management on ecosystem services. However, these are generally not available on farm/field scale. To close this gap, we present an agent-based model for Fertilization In Grasslands (FertIG). Based on animal, land-use, and cutting data, the model estimates grassland yields and calculates field-specific amounts of applied organic and mineral nitrogen on grassland (and partly cropland). Furthermore, the model considers different legal requirements (including fertilization ordinances) and nutrient trade among farms. FertIG was applied to a grassland-dominated region in Bavaria, Germany comparing the effects of changes in the fertilization ordinance as well as nutrient trade. The results show that the consideration of nutrient trade improves organic fertilizer distribution and leads to slightly lower Nmin applications. On a regional scale, recent legal changes (fertilization ordinance) had limited impacts. Limiting the maximum applicable amount of Norg to 170 kg N/ha fertilized area instead of farm area as of 2020 hardly changed fertilizer application rates. No longer considering application losses in the calculation of fertilizer requirements had the strongest effects, leading to lower supplementary Nmin applications. The model can be applied to other regions in Germany and, with respective adjustments, in Europe. Generally, it allows comparing the effects of policy changes on fertilization management at regional, farm and field scale.

This model uses preference rankings w.r.t. ethnic group compositions (e.g. at companies) and assigns ethnic agents to groups based on their rankings.

A group of agents share a resource and agents will become sufficiently motivated to adopt a rule to constraint their freedom if they experience resource scarcity and developed mutual trust relationships.

Positive feedback can lead to “trapping” in local optima. Adding a simple negative feedback effect, based on ant behaviour, prevents this trapping

Models land-use, perception, and biocultural interactions between two forager populations.

Three policy scenarios for urban expansion under the influences of the behaviours and decision modes of four agents and their interactions have been applied to predict the future development patterns of the Guangzhou metropolitan region.

The model is based on the influence function of the Leviathan model (Deffuant, Carletti, Huet 2013 and Huet and Deffuant 2017) with the addition of group idenetity. We aim at better explaining some patterns generated by this model, using a derived mathematical approximation of the evolution of the opinions averaged.

We consider agents having an opinion/esteem about each other and about themselves. During dyadic meetings, agents change their respective opinion about each other, and possibly about other agents they gossip about, with a noisy perception of the opinions of their interlocutor. Highly valued agents are more influential in such encounters. Moreover, each agent belongs to a single group and the opinions within the group are attracted to their average.

We show that a group hierarchy can emerges from this model, and that the inequality of reputations among groups have a negative effect on the opinions about the groups of low status. The mathematical analysis of the opinion dynamic shows that the lower the status of the group, the more detrimental the interactions with the agents of other groups are for the opinions about this group, especially when gossip is activated. However, the interactions between agents of the same group tend to have a positive effect on the opinions about this group.

We employ this spatially explicit agent-based model to begin to examine how time-averaging can affect the spatial scale of cultural similarity in archaeological assemblage data. The model was built to address this question: to what extent does time-averaging affect the scale of local spatial association in the relative frequency of the most prevalent cultural variant in an archaeological landscape?

An agent-based model of individual consumers making choices between five possible diets: omnivore, flexitarian, pescatarian, vegetarian, or vegan. Each consumer makes decisions based on personal constraints and values, and their perceptions of how well each diet matches with those values. Consumers can also be influenced by each other’s perceptions via interaction across three social networks: household members, friends, and acquaintances.