Protein 2.0 is a systems model of the Norwegian protein sector designed to explore the potential impacts of carbon taxation and the emergence of cultivated meat and dairy technologies. The model simulates production, pricing, and consumption dynamics across conventional and cultivated protein sources, accounting for emissions intensity, technological learning, economies of scale, and agent behaviour. It assesses how carbon pricing could alter the competitiveness of conventional beef, lamb, pork, chicken, milk, and egg production relative to emerging cultivated alternatives, and evaluates the implications for domestic production, emissions, and food system resilience. The model provides a flexible platform for exploring policy scenarios and transition pathways in protein supply. Further details can be found in the associated publication.

Package for simulating the behavior of experts in a scientific-forecasting competition, where the outcome of experiments itself depends on expert consensus. We pay special attention to the interplay between expert bias and trust in the reward algorithm. The package allows the user to reproduce results presented in arXiv:2305.04814, as well as testing of other different scenarios.

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.

Simulates the construction of scientific journal publications, including authors, references, contents and peer review. Also simulates collective learning on a fitness landscape. Described in: Watts, Christopher & Nigel Gilbert (forthcoming) “Does cumulative advantage affect collective learning in science? An agent-based simulation”, Scientometrics.

Must tax-benefit policy making be limited to the ‘experts’?

An Agent-based model simulates consumer demand for Smart Metering tariffs. It utilizes the Bass Diffusion Model and Rogers´s adopter categories. Integration of empirical census microdata enables a validated socio-economic background for each consumer.

A System Dynamics Model to anticipate insurgent movements and policy design to handle them .

An ABM to simulate the behaviour of households within a village and observe the emerging properties of the system in terms of food security. The model quantifies food availability, access, utilisation and stability.

The model’s purpose is to provide a potential explanation for the emergence, sustenance and decline of unpopular norms based on pluralistic ignorance on a social network.

In this model, we simulate the navigation behavior of homing pigeons. Specifically we use genetic algorithms to optimize the navigation and flocking parameters of pigeon agents.