This is an agent-based model constructed in Netlogo v6.2.2 which seeks to provide a simple but flexible tool for researchers and dog-population managers to help inform management decisions.

It replicates the basic demographic processes including:
* reproduction
* natural death
* dispersal
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Country-by-Country Reporting and Automatic Exchange of Information have recently been implemented in European Union (EU) countries. These international tax reforms increase tax compliance in the short term. In the long run, however, taxpayers will continue looking abroad to avoid taxation and, countries, looking for additional revenues, will provide opportunities. As a result, tax competition intensifies and the initial increase in compliance could reverse. To avoid international tax reforms being counteracted by tax competition, this paper suggests bilateral responsive regulation to maximize compliance. This implies that countries would use different tax policy instruments toward other countries, including tax and secrecy havens.

To assess the effectiveness of fully or partially enforce tax policies, this agent based model has been ran many times under different enforcement rules, which influence the perceived enforced- and voluntary compliance, as the slippery-slope model prescribes. Based on the dynamics of this perception and the extent to which agents influence each other, the annual amounts of tax evasion, tax avoidance and taxes paid are calculated over longer periods of time.

The agent-based simulation finds that a differentiated policy response could increase tax compliance by 6.54 percent, which translates into an annual increase of €105 billion in EU tax revenues on income, profits, and capital gains. Corporate income tax revenues in France, Spain, and the UK alone would already account for €35 billion.

This is a replication of the SequiaBasalto model, originally built in Cormas by Dieguez Cameroni et al. (2012, 2014, Bommel et al. 2014 and Morales et al. 2015). The model aimed to test various adaptations of livestock producers to the drought phenomenon provoked by climate change. For that purpose, it simulates the behavior of one livestock farm in the Basaltic Region of Uruguay. The model incorporates the price of livestock, fodder and paddocks, as well as the growth of grass as a function of climate and seasons (environmental submodel), the life cycle of animals feeding on the pasture (livestock submodel), and the different strategies used by farmers to manage their livestock (management submodel). The purpose of the model is to analyze to what degree the common management practices used by farmers (i.e., proactive and reactive) to cope with seasonal and interannual climate variations allow to maintain a sustainable livestock production without depleting the natural resources (i.e., pasture). Here, we replicate the environmental and livestock submodel using NetLogo.

One year is 368 days. Seasons change every 92 days. Each day begins with the growth of grass as a function of climate and season. This is followed by updating the live weight of cows according to the grass height of their patch, and grass consumption, which is determined based on the updated live weight. After consumption, cows grow and reproduce, and a new grass height is calculated. Cows then move to the patch with less cows and with the highest grass height. This updated grass height value will be the initial grass height for the next day.

Viable North Sea (ViNoS) is an Agent-based Model of the German North Sea Small-scale Fisheries in a Social-Ecological Systems framework focussing on the adaptive behaviour of fishers facing regulatory, economic, and resource changes. Small-scale fisheries are an important part both of the cultural perception of the German North Sea coast and of its fishing industry. These fisheries are typically family-run operations that use smaller boats and traditional fishing methods to catch a variety of bottom-dwelling species, including plaice, sole, and brown shrimp. Fisheries in the North Sea face area competition with other uses of the sea – long practiced ones like shipping, gas exploration and sand extractions, and currently increasing ones like marine protection and offshore wind farming. German authorities have just released a new maritime spatial plan implementing the need for 30% of protection areas demanded by the United Nations High Seas Treaty and aiming at up to 70 GW of offshore wind power generation by 2045. Fisheries in the North Sea also have to adjust to the northward migration of their established resources following the climate heating of the water. And they have to re-evaluate their economic balance by figuring in the foreseeable rise in oil price and the need for re-investing into their aged fleet.

The Olympic Peninsula ABM works as a virtual laboratory to simulate the existing forestland management practices as followed by different forestland owner groups in the Olympic Peninsula, Washington, and explore how they could shape the future provisions of multifunctional ecosystem services such as Carbon storage and revenue generation under the business-as-usual scenario as well as by their adaptation to interventions. Forestlands are socio-ecological systems that interact with economic, socio-cultural, and policy systems. Two intervention scenarios were introduced in this model to simulate the adaptation of landowner behavior and test the efficacy of policy instruments in promoting sustainable forest practices and fostering Carbon storage and revenue generation. (1) A market-linked carbon offset scheme that pays the forestland owners a financial incentive in the form of a yearly carbon rent. (2) An institutional intervention policy that allows small forest owners (SFLO) to cooperate for increased market access and benefits under carbon rent scenario. The model incorporates the heterogeneous contexts within which the forestland owners operate and make their forest management decisions by parameterizing relevant agent attributes and contextualizing their unique decision-making processes.

This is NetLogo code that presents two alternative implementations of Correlated Random Walk (CRW):
- 1. drawing the turning angles from the uniform distribution, i.e. drawing the angle with the same probability from a certain given range;
- 2. drawing the turning angles from von Mises distribution.
The move lengths are drawn from the lognormal distribution with the specified parameters.

Correlated Random Walk is used to represent the movement of animal individuals in two-dimensional space. When modeled as CRW, the direction of movement at any time step is correlated with the direction of movement at the previous time step. Although originally used to describe the movement of insects, CRW was later shown to sufficiently well describe the empirical movement data of other animals, such as wild boars, caribous, sea stars.
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An Agent-Based Model to simulate agent reactions to threatening information based on the anxiety-to-approach framework of Jonas et al. (2014).
The model showcases the framework of BIS/BAS (inhibitory and approach motivated behavior) for the case of climate information, including parameters for anxiety, environmental awareness, climate scepticism and pro-environmental behavior intention.

Agents receive external information according to threat-level and information frequency. The population dynamic is based on the learning from that information as well as social contagion mechanisms through a scale-free network topology.

The model uses Netlogo 6.2 and the network extension.
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This version 2.1.0 of the uFunk model is about setting a business strategy (the S in the name) for an organization. A team of managers (or executives) meet and discuss various options on the strategy for the firm. There are three aspects that they have to agree on to set the strategic positioning of the organization.
The discussion is on market, stakeholders, and resources. The team (it could be a business strategy task force) considers various aspects of these three elements. The resources they use to develop the discussion can come from a traditional approach to strategy or from non-traditional means (e.g., so-called serious play, creativity and imagination techniques).
The S-uFunk 2.1.0 Model wants to understand to which extent cognitive means triggered by traditional and non-traditional resources affect the making of the strategy process.

The Social Identity Model of Protest Emergence (SIMPE), an agent-based model of national identity and protest mobilisations.

I developed this model for my PhD project, “Polarisation and Protest Mobilisation Around Secessionist Movements: an Agent-Based Model of Online and Offline Social Networks”, at the University of Glasgow (2019-2023).

The purpose of this model is to simulate protest emergence in a given country where there is an independence movement, fostering the self-categorisation process of national identification. In order to contextualised SIMPE, I have used Catalonia, where an ongoing secessionist movement since 2011 has been present, national identity has shown signs of polarisation, and where numerous mobilisations have taken place over the last decade. Data from the Catalan Centre of Opinion Studies (CEO) has been used to inform some of the model parameters.

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This model is an implementation of a predator-prey simulation using NetLogo programming language. It simulates the interaction between fish, lionfish, and zooplankton. Fish and lionfish are both represented as turtles, and they have their own energy level. In this simulation, lionfish eat fish, and fish eat zooplankton. Zooplankton are represented as green patches on the NetLogo world. Lionfish and fish can reproduce and gain energy by eating other turtles or zooplankton.

This model was created to help undergraduate students understand how simulation models might be helpful in addressing complex environmental problems. In this case, students were asked to use this model to make predictions about how the introduction of lionfish (considered an invasive species in some places) might alter the ecosystem.