Our mission is to help computational modelers develop, document, and share their computational models in accordance with community standards and good open science and software engineering practices. Model authors can publish their model source code in the Computational Model Library with narrative documentation as well as metadata that supports open science and emerging norms that facilitate software citation, computational reproducibility / frictionless reuse, and interoperability. Model authors can also request private peer review of their computational models. Models that pass peer review receive a DOI once published.
All users of models published in the library must cite model authors when they use and benefit from their code.
Please check out our model publishing tutorial and feel free to contact us if you have any questions or concerns about publishing your model(s) in the Computational Model Library.
We also maintain a curated database of over 7500 publications of agent-based and individual based models with detailed metadata on availability of code and bibliometric information on the landscape of ABM/IBM publications that we welcome you to explore.
Displaying 10 of 376 results for "Huw Vasey" clear search
This model aims to examine how different levels of communication noise and superiority bias affect team performance when solving problems collectively. We used a networked agent-based model of collective problem solving in which agents explore the NK landscape for a better solution and communicate with each other regarding their current solutions. We compared the team performance in solving problems collectively at different levels of self-superiority bias when facing simple and complex problems. Additionally, we addressed the effect of different levels of communication noise on the team’s outcome
This model simulates diffusion curves and it allows to test how social influence, network structure and consumer heterogeneity affect their spreads and their speeds.
RAGE models a stylized common property grazing system. Agents follow a certain behavioral type. The model allows analyzing how household behavior with respect to a social norm on pasture resting affects long-term social-ecological system dynamics.
The purpose of the model is to investigate how different factors affect the ability of researchers to reconstruct prehistoric social networks from artifact stylistic similarities, as well as the overall diversity of cultural traits observed in archaeological assemblages. Given that cultural transmission and evolution is affected by multiple interacting phenomena, our model allows to simultaneously explore six sets of factors that may condition how social networks relate to shared culture between individuals and groups:
This MAS simulates the traffic of Barcelona Eixample. Uses a centralized AI system in order to control the traffic lights. Car agents are reactive and have no awareness of the intelligence of the system. They (try to) avoid collisions.
The MOBILITY model analyzes how agents’ mobility affects the performance of social-ecological systems in different landscape configurations.
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 model simulates how collective self-organisation among individuals that manage irrigation resource collectively.
The model is intended to simulate visitor spatial and temporal dynamics, encompassing their numbers, activities, and distribution along a coastline influenced by beach landscape design. Our primary focus is understanding how the spatial distribution of services and recreational facilities (e.g., beach width, entrance location, recreational facilities, parking availability) impacts visitation density. Our focus is not on tracking the precise visitation density but rather on estimating the areas most affected by visitor activity. This comprehension allows for assessing the diverse influences of beach layouts on spatial visitor density and, consequently, on the landscape’s biophysical characteristics (e.g., vegetation, fauna, and sediment features).
This agent-based model simulates the implementation of a Transfer of Development Rights (TDR) mechanism in a stylized urban environment inspired by Dublin. It explores how developer agents interact with land parcels under spatial zoning, conservation protections, and incentive-based policy rules. The model captures emergent outcomes such as compact growth, green and heritage zone preservation, and public cost-efficiency. Built in NetLogo, the model enables experimentation with variable FSI bonuses, developer behavior, and spatial alignment of sending/receiving zones. It is intended as a policy sandbox to test market-aligned planning tools under behavioral and spatial uncertainty.
Displaying 10 of 376 results for "Huw Vasey" clear search