Overview

The Weather model is a procedural generation model designed to create realistic daily weather data for socioecological simulations. It generates synthetic weather time series for solar radiation, temperature, and precipitation using algorithms based on sinusoidal and double logistic functions. The model incorporates stochastic variation to mimic unpredictable weather patterns and aims to provide realistic yet flexible weather inputs for exploring diverse climate scenarios.

The Weather model can be used independently or integrated into larger models, providing realistic weather patterns without extensive coding or data collection. It can be customized to meet specific requirements, enabling users to gain a better understanding of the underlying mechanisms and have greater confidence in their applications.

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The model’s aim is to represent the price dynamics under very simple market conditions, given the values adopted by the user for the model parameters. We suppose the market of a financial asset contains agents on the hypothesis they have zero-intelligence. In each period, a certain amount of agents are randomly selected to participate to the market. Each of these agents decides, in a equiprobable way, between proposing to make a transaction (talk = 1) or not (talk = 0). Again in an equiprobable way, each participating agent decides to speak on the supply (ask) or the demand side (bid) of the market, and proposes a volume of assets, where this number is drawn randomly from a uniform distribution. The granularity depends on various factors, including market conventions, the type of assets or goods being traded, and regulatory requirements. In some markets, high granularity is essential to capture small price movements accurately, while in others, coarser granularity is sufficient due to the nature of the assets or goods being traded

Agents are linked in a social-network and make decisions on which of 2 types of behavior to adopt. We explore consequences of different information feedback and providing targeted feedback to individuals.

This is a simple model replicating Hardin’s Tragedy of the Commons using reactive agents that have psychological behavioral and social preferences.

Models land-use, perception, and biocultural interactions between two forager populations.

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

This model can be used to optimize intervention strategies for inspection services.

The purpose of the model is to simulate the cultural hitchhiking hypothesis to explore how neutral cultural traits linked with advantageous traits spread together over time

This is an agent-based model designed to explore the evolution of cooperation under changes in resources availability for a given population

Lakeland 2 is a simple version of the original Lakeland of Jager et al. (2000) Ecological Economics 35(3): 357-380. The model can be used to explore the consequences of different behavioral assumptions on resource and social dynamics.