This is a stylised agent-based model designed to explore the conditions that lead to lock-ins and transitions in agri-food systems.

The model represents interactions between four different types of agents: farmers, consumers, markets, and the state. Farmers and consumers are heterogeneous, and at each time step decide whether to trade with one of two market agents: the conventional or alternative. The state agent provides subsidies to the farmers at each time step.

The key emergent outcome is the fraction of trade in each time step that flows through the alternative market agent. This arises from the distributed decisions of farmer and consumer agents. A “sustainability transition” is defined as a shift in the dominant practices (and associated balance of power) towards the alternative paradigm.

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This model simulates the dynamics of agricultural land use change, specifically the transition between agricultural and non-agricultural land use in a spatial context. It explores the influence of various factors such as agricultural profitability, path dependency, and neighborhood effects on land use decisions.

The model operates on a grid of patches representing land parcels. Each patch can be in one of two states: exploited (green, representing agricultural land) or unexploited (brown, representing non-agricultural land). Agents (patches) transition between these states based on probabilistic rules. The main factors affecting these transitions are agricultural profitability, path dependency, and neighborhood effects.
-Agricultural Profitability: This factor is determined by the prob-agri function, which calculates the probability of a non-agricultural patch converting to agricultural based on income differences between agriculture and other sectors. -Path Dependency: Represented by the path-dependency parameter, it influences the likelihood of patches changing their state based on their current state. It’s a measure of inertia or resistance to change. -Neighborhood Effects: The neighborhood function calculates the number of exploited (agricultural) neighbors of a patch. This influences the decision of a patch to convert to agricultural land, representing the influence of surrounding land use on the decision-making process.

We introduce a model of prediction markets that uses opinion dynamics as its underlying mechanism for price formation. We base the opinion dynamics on the Deffuant model of bounded rationality. We have used this model to show that price formation in prediction markets can be robustly explained by opinion dynamics, and that the model can also explain phase transitions depending on just two parameters.

A model of the emergence of intersectional life course inequalities through transitions in the workplace. It explores LGBTQ citizens’ career outcomes and trajectories in relation to several mediating factors: (i) workplace discrimination; (ii) social capital; (iii) policy interventions (i.e., workplace equality, diversity, and inclusion policies); (iv) and LGBTQ employees’ behaviours in response to discrimination (i.e., moving workplaces and/or different strategies for managing the visibility of their identity).

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.

The TERROIR agent-based model was built for the multi-level analysis of biomass and nutrient flows within agro-sylvo-pastoral villages in West Africa. It explicitly takes into account both human organization and spatial extension of such flows.

This model implements a classic scenario used in Reinforcement Learning problem, the “Cliff Walking Problem”. Consider the gridworld shown below (SUTTON; BARTO, 2018). This is a standard undiscounted, episodic task, with start and goal states, and the usual actions causing movement up, down, right, and left. Reward is -1 on all transitions except those into the region marked “The Cliff.” Stepping into this region incurs a reward of -100 and sends the agent instantly back to the start (SUTTON; BARTO, 2018).

The problem is solved in this model using the Q-Learning algorithm. The algorithm is implemented with the support of the NetLogo Q-Learning Extension

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.

ACT is an ABM based on an existing conceptualisation of the concept of critical transitions applied to the energy transition. With the model we departed from the mean-field approach simulated relevant actor behaviour in the energy transition.

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