How does the world population adapt its policies on energy when it is confronted with a climate change? This model combines a climate-economy model with adaptive agents.

FNNR-ABM is an agent-based model that simulates human activity, Guizhou snub-nosed monkey movement, and GTGP-enrolled land parcel conversion in the Fanjingshan National Nature Reserve in Guizhou, China.

Quick-start guide:
1. Install Python and set environmental path variables.
2. Install the mesa, matplotlib (optional), and pyshp (optional) Python libraries.
3. Configure fnnr_config_file.py.
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A dynamic identity model for misinformation in social networks, an agent-based model of social identity and misinformation dynamics.

I developed this model as a part of my master’s thesis, “Does social identity drive belief and persistence in online misinformation? An agent-based modelling approach” at University College Dublin, Ireland (2024-2025).

The purpose of this model is to further understand the dynamics of misinformation sharing as an expression of social identity. I introduce a framework to understand the influence of self-categorisation on misinformation persistence in social network. It integrates a social learning model with the Dynamic Identity Model for Agents (DIMA) using simple logic to simulate the social trade-offs driving misinformation and observe the effects on misinformation spread.

EffLab was built to support the study of the efficiency of agents in an evolving complex adaptive system. In particular:
- There is a definition of efficiency used in ecology, and an analogous definition widely used in business. In ecological studies it is called EROEI (energy returned on energy invested), or, more briefly, EROI (pronounced E-Roy). In business it is called ROI (dollars returned on dollars invested).
- In addition, there is the more well-known definition of efficiency first described by Sadi Carnot, and widely used by engineers. It is usually represented by the Greek letter ‘h’ (pronounced as ETA). These two measures of efficiency bear a peculiar relationship to each other: EROI = 1 / ( 1 - ETA )

In EffLab, blind seekers wander through a forest looking for energy-rich food. In this multi-generational world, they live and reproduce, or die, depending on whether they can find food more effectively than their contemporaries. Data is collected to measure their efficiency as they evolve more effective search patterns.

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