We present an Agent-Based Stock Flow Consistent Multi-Country model of a Currency Union to analyze the impact of changes in the fiscal regimes that is permanent changes in the deficit-to-GDP targets that governments commit to comply.

For deep decarbonisation, the design of climate policy needs to account for consumption choices being influenced not only by pricing but also by social learning. This involves changes that pertain to the whole spectrum of consumption, possibly involving shifts in lifestyles. In this regard, it is crucial to consider not just short-term social learning processes but also slower, longer-term, cultural change. Against this background, we analyse the interaction between climate policy and cultural change, focusing on carbon taxation. We extend the notion of “social multiplier” of environmental policy derived in an earlier study to the context of multiple consumer needs while allowing for behavioural spillovers between these, giving rise to a “cultural multiplier”. We develop a model to assess how this cultural multiplier contributes to the effectiveness of carbon taxation. Our results show that the cultural multiplier stimulates greater low-carbon consumption compared to fixed preferences. The model results are of particular relevance for policy acceptance due to the cultural multiplier being most effective at low-carbon tax values, relative to a counter-case of short-term social interactions. Notably, at high carbon tax levels, the distinction between social and cultural multiplier effects diminishes, as the strong price signal drives even resistant individuals toward low-carbon consumption. By varying socio-economic conditions, such as substitutability between low- and high-carbon goods, social network structure, proximity of like-minded individuals and the richness of consumption lifestyles, the model provides insight into how cultural change can be leveraged to induce maximum effectiveness of climate policy.

This Python module contain a function that is able to test the ergodicity of a given agent based model. It is sufficient to produce one long time series and many smaller time series. The function uses

This is the R code of the mathematical model that includes the decision making formulations for artificial agents. This code corresponds to equations 1-70 given in the paper “A Mathematical Model of The Beer Game”.

Toolkit to specify demographic multistate model with a behavioural element linking intentions to behaviour

IOP 2.1.2 is an agent-based simulation model designed to explore the relations between (1) employees, (2) tasks and (3) resources in an organizational setting. By comparing alternative cognitive strategies in the use of resources, employees face increasingly demanding waves of tasks that derive by challenges the organization face to adapt to a turbulent environment. The assumption tested by this model is that a successful organizational adaptation, called plastic, is necessarily tied to how employees handle pressure coming from existing and new tasks. By comparing alternative cognitive strategies, connected to ‘docility’ (Simon, 1993; Secchi, 2011) and ‘extended’ cognition (Clark, 2003, Secchi & Cowley, 2018), IOP 2.1.2 is an attempt to indicate which strategy is most suitable and under which scenario.

This model is designed to show the effects of personality types and student organizations have on ones chance to making friendships in a university setting. As known from psychology studies, those that are extroverted have an easier chance making friendships in comparison to those that are introverted.
Once every tick a pair of students (nodes) will be randomly selected they will then have the chance to either be come friends or not (create an edge or not) based on their personality type (you are able to change what the effect of each personality is) and whether or not they are in the same club (you can change this value) then the model triggers the next tick cycle to begin.

Social distancing is a strategy to mitigate the spread of contagious disease, but it bears negative impacts on people’s social well-being, resulting in non-compliance. This paper uses an integrated behavioral simulation model, called HUMAT, to identify a sweet spot
that balances strictness of and obedience to social distancing rules.

A novel agent-based model was developed that aims to explore social interaction while it is constrained by visitor limitations (due to Dutch COVID measures). Specifically, the model aims to capture the interaction between the need for social contact and the support for the visitors measure. The model was developed using the HUMAT integrated framework, which offered a psychological and sociological foundation for the behavior of the agents.

This generic model simulates climate change adaptation in the form of resistance, accommodation, and retreat in coastal regions vulnerable to sea level rise and flooding. It tracks how population changes as households retreat to higher ground.

A fisher directed management system was describeded by Hart (2021). It was proposed that fishers should only be allowed to exploit a resource if they collaborated in a resource management system for which they would own and be collectively responsible for. As part of the system fishers would need to follow the rules of exploitation set by the group and provide a central unit with data with which to monitor the fishery. Any fisher not following the rules would at first be fined but eventually expelled from the fishery if he/she continued to act selfishly. This version of the model establishes the dynamics of a fleet of vessels and controls overfishing by imposing fines on fishers whose income is low and who are tempted to keep fishing beyond the set quota which is established each year depending on the abundance of the fish stock. This version will later be elaborated to have interactions between the fishers including pressure to comply with the norms set by the group and which could lead to a stable management system.