CoMSES Net maintains cyberinfrastructure to foster FAIR data principles for access to and (re)use of computational models. Model authors can publish their model code in the Computational Model Library with documentation, metadata, and data dependencies and support these FAIR data principles as well as best practices for software citation. Model authors can also request that their model code be peer reviewed to receive a DOI. All users of models published in the library must cite model authors when they use and benefit from their code.
CoMSES Net also maintains a curated database of over 7500 publications of agent-based and individual based models with additional metadata on availability of code and bibliometric information on the landscape of ABM/IBM publications that we welcome you to explore.
A simulated approach for Personal Carbon Trading, for figuring out what effects it might have if it will be implemented in the real world. We use an artificial population with some empirical data from international literature and basic assumptions about heterogeneous energy demand. The model is not to be used as simulating the actual behavior of real populations, but a toy model to test the effects of differences in various factors such as number of agents, energy price, price of allowances, etc. It is important to adapt the model for specific countries as carbon footprint and energy demand determines the relative success of PCT.
We compare three model estimates for the time and treatment requirements to eliminate HCV among HIV-positive MSM in Victoria, Australia: a compartmental model; an ABM parametrized by surveillance data; and an ABM with a more heterogeneous population.
The CONSERVAT model evaluates the effect of social influence among farmers in the Lake Naivasha basin (Kenya) on the spatiotemporal diffusion pattern of soil conservation effort levels and the resulting reduction in lake sedimentation.
The model simulates seven agents engaging in collective action and inter-network social learning. The objective of the model is to demonstrate how mental models of agents can co-evolve through a complex relationship among factors influencing decision-making, such as access to knowledge and personal- and group-level constraints.
This abstract model explores the emergence of altruistic behavior in networked societies. The model allows users to experiment with a number of population-level parameters to better understand what conditions contribute to the emergence of altruism.
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 combines agent-based modelling and microeconomic approach to simulate the decision behaviour of land developers and how this impacts on the spatio-temporal processes of urban expansion.
In the consumer advice network, users with connections can interact with each other, and the network topology will change during the opinion interaction. When the opinion distance from i to j is greater than the confidence threshold, the two consumers cannot exchange opinions, and the link between them will disconnect with probability DE. Then, a link from node i to node k is established with probability CE and node i learning opinion from node k.