Our mission is to help computational modelers at all levels engage in the establishment and adoption of community standards and good practices for developing and sharing computational models. Model authors can freely publish their model source code in the Computational Model Library alongside narrative documentation, open science metadata, and other emerging open science norms that facilitate software citation, reproducibility, interoperability, and reuse. Model authors can also request peer review of their computational models to receive a DOI.
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 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 additional 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 162 results for "Mark R Kramer" clear search
I model a forest and a community of loggers. Agents follow different kinds of rules in order to log. I compare the impact of endogenous and of exogenous institutions on the state of the forest and on the profit of the users, representing different scenarios of participatory conservation projects.
This model is designed to investigate the impact of alternative policy approaches and changing land tenure dynamics on farmer adoption of conservation practices intended to increase the water quality.
This is an agent-based model that simulates the structural evolution in food supply chain.
The purpose of this model is to understand the role of trade networks and their interaction with different fish resources, for fish provision. The model is developed based on a multi-methods approach, combining agent-based modeling, network analysis and qualitative data based on a small-scale fisheries study case. The model can be used to investigate both how trade network structures are embedded in a social-ecological context and the trade processes that occur within them, to analyze how they lead to emergent outcomes related to the resilience of fish provision. The model processes are informed by qualitative data analysis, and the social network analysis of an empirical fish trade network. The network analysis can be used to investigate diverse network structures to perform model experiments, and their influence on model outcomes.
The main outcomes we study are 1) the overexploitation of fish resources and 2) the availability and variability of fish provision to satisfy different market demands, and 3) individual traders’ fish supply at the micro-level. The model has two types of trader agents, seller and dealer. The model reveals that the characteristics of the trade networks, linked to different trader types (that have different roles in those networks), can affect the resilience of fish provision.
This is a generic sub-model of animal territory formation. It is meant to be a reusable building block, but not in the plug-and-play sense, as amendments are likely to be needed depending on the species and region. The sub-model comprises a grid of cells, reprenting the landscape. Each cell has a “quality” value, which quantifies the amount of resources provided for a territory owner, for example a tiger. “Quality” could be prey density, shelter, or just space. Animals are located randomly in the landscape and add grid cells to their intial cell until the sum of the quality of all their cells meets their needs. If a potential new cell to be added is owned by another animal, competition takes place. The quality values are static, and the model does not include demography, i.e. mortality, mating, reproduction. Also, movement within a territory is not represented.
This model is programmed in Python 3.6. We model how different consensus protocols and trade network topologies affect the performance of a blockchain system. The model consists of multiple trader and miner agents (Trader.py and Tx.py), and one system agent (System.py). We investigated three consensus protocols, namely proof-of-work (PoW), proof-of-stake (PoS), and delegated proof-of-stake (DPoS). We also examined three common trade network topologies: random, small-world, and scale-free. To reproduce our results, you may need to create some databases using, e.g., MySQL; or read and write some CSV files as model configurations.
A stylized scale model to codesign with villagers an agent-based model of bushmeat hunting in the periphery of Korup National Park (Cameroon)
Industrial clustering patterns are the result of an entrepreneurial process where spinoffs inherit the ideas and attributes of their parent firms. This computational model maps these patterns using abstract methodologies.
This repository contains: (1) a model calibration procedure that identifies a set of diverse, plausible models; and (2) an ABM of smallholder agriculture, which is used as a case study application for the calibration method. By identifying a set of diverse models, the calibration method attends to the issue of “equifinality” prevalent in complex systems, which is a situation where multiple plausible process descriptions exist for a single outcome.
Due to the large extent of the Harz National Park, an accurate measurement of visitor numbers and their spatiotemporal distribution is not feasible. This model demonstrates the possibility to simulate the streams of visitors with ABM methodology.
Displaying 10 of 162 results for "Mark R Kramer" clear search