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.

This model aims to investigate how different type of learning (social system) and disturbance specific attributes (ecological system) influence adoption of treatment strategies to treat the effects of ecological disturbances.

The model explores the impact of journal metrics (e.g., the notorious impact factor) on the perception that academics have of an article’s scientific value.

This model simulates networking mechanisms of an empirical social network. It correlates event determinants with place-based geography and social capital production.

This model simulates the spread of anti-vaccine sentiments in cyber and physical space and how it creates emergence of clusters of anti-vacciners, which eventually lead to higher probablity of disease outbreaks.

The aim of this model is to explore and understand the factors driving adoption of treatment strategies for ecological disturbances, considering payoff signals, learning strategies and social-ecological network structure

This model makes it possible to explore how network clustering and resistance to changing existing status beliefs might affect the spontaneous emergence and diffusion of such beliefs as described by status construction theory.

The model studies the dynamics of risk-sharing cooperatives among heterogeneous farmers. Based on their knowledge on their risk exposure and the performance of the cooperative farmers choose whether or not to remain in the risk-sharing agreement.

The objective of the model is to evaluate the impact of seasonal forecasts on a farmer’s net agricultural income when their crop choices have different and variable costs and returns.

We propose an agent-based model where a fixed finite population of tagged agents play iteratively the Nash demand game in a regular lattice. The model extends the bargaining model by Axtell, Epstein and Young.