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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We build a stylized model of a network of business angel investors and start-up entrepreneurs. Decisions are based on trust as a decision making tool under true uncertainty.

The model explores the emergence of inequality in cognitive and socio-emotional skills at the societal level within and across generations that results from differences in parental investment behavior during childhood and adolescence.

We demonstrate how Repast Simphony statecharts can efficiently encapsulate the deep classification hierarchy of the U.S. Air Force for manpower life cycle costing.

This model simulates the lithic raw material use and provisioning behavior of a group that inhabits a permanent base camp, and uses stone tools.

This agent-based model represents a stylized inter-organizational innovation network where firms collaborate with each other in order to generate novel organizational knowledge.

The program simulate the functioning of an italian health and social public information office (SPUN) on the basis of the real data collected in the first five years of functioning.

A modelling system to simulate Neanderthal demography and distribution in a reconstructed Western Europe for the late Middle Paleolithic.

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.

In recent years we have seen multiple incidents with a large number of people injured and killed by one or more armed attackers. Since this type of violence is difficult to predict, detecting threats as early as possible allows to generate early warnings and reduce response time. In this context, any tool to check and compare different action protocols can be a further step in the direction of saving lives. Our proposal combines features from continuous and discrete models to obtain the best of both worlds in order to simulate large and crowded spaces where complex behavior individuals interact. With this proposal we aim to provide a tool for testing different security protocols under several emergency scenarios, where spaces, hazards, and population can be customized. Finally, we use a proof of concept implementation of this model to test specific security protocols under emergency situations for real spaces. Specifically, we test how providing some users of a university college with an app that informs about the type and characteristics of the ongoing hazard, affects in the safety performance.