The simulation model LAMDA investigates the influences of varying cognitive abilities of the decision maker on the truth-inducing effect of the Groves mechanism. Bounded rationality concepts are represented by information states and learning models.

The MOBILITY model analyzes how agents’ mobility affects the performance of social-ecological systems in different landscape configurations.

WWHW is an agent-based model designed to allow the exploration of the emergence, resilience and evolution of cooperative behaviours in hunter-fisher-gatherer societies.

Demand planning requires processing of distributed information. In this process, individuals, their properties and interactions play a crucial role. This model is a computational testbed to investigate these aspects with respect to forecast accuracy.

The model simulates interaction between internal physiological factors (e.g. energy balance) and external social factors (e.g. competition level) underlying feeding and social interaction behaviour of commercially group-housed pigs.

Patagonia PSMED is an agent-based model designed to study a simple case of Evolution of Ethnic Differentiation. It replicates how can hunter-gatherer societies evolve and built cultural identities as a consequence of the way they interacted.

The model simulates agents in a spatial environment competing for a common resource that grows on patches. The resource is converted to energy, which is needed for performing actions and for surviving.

A first version of a model that describes how coalitions are formed during open, networked innovation

The simulation model SimPLS shows an application of the PLS agent concept, using SEM as empirical basis for the definition of agent architectures. The simulation model implements the PLS path model TAM about the decision of using innovative products.

The current rate of production and consumption of meat poses a problem both to peoples’ health and to the environment. This work aims to develop a simulation of peoples’ meat consumption behaviour in Britain using agent-based modelling. The agents represent individual consumers. The key variables that characterise agents include sex, age, monthly income, perception of the living cost, and concerns about the impact of meat on the environment, health, and animal welfare. A process of peer influence is modelled with respect to the agents’ concerns. Influence spreads across two eating networks (i.e. co-workers and household members) depending on the time of day, day of the week, and agents’ employment status. Data from a representative sample of British consumers is used to empirically ground the model. Different experiments are run simulating interventions of application of social marketing campaigns and a rise in price of meat. The main outcome is the average weekly consumption of meat per consumer. A secondary outcome is the likelihood of eating meat.