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 64 results for "Stephanie Kramer-Schadt" clear search
Three policy scenarios for urban expansion under the influences of the behaviours and decision modes of four agents and their interactions have been applied to predict the future development patterns of the Guangzhou metropolitan region.
Status-power dynamics on a playground, resulting in a status landscape with a gender status gap. Causal: individual (beauty, kindness, power), binary (rough-and-tumble; has-been-nice) or prior popularity (status). Cultural: acceptability of fighting.
WeDiG Sim- Weighted Directed Graph Simulator - is an open source application that serves to simulate complex systems. WeDiG Sim reflects the behaviors of those complex systems that put stress on scale-free, weightedness, and directedness. It has been implemented based on “WeDiG model” that is newly presented in this domain. The WeDiG model can be seen as a generalized version of “Barabási-Albert (BA) model”. WeDiG not only deals with weighed directed systems, but also it can handle the […]
This model represnts an unique human-aquifer interactions model for the Li-extraction in Salar de Atacama, Chile. It describes the local actors’ experience of mining-induced changes in the socio-ecological system, especially on groundwater changes and social stressors. Social interactions are designed specifically according to a long-term local fieldwork by Babidge et al. (2019, 2020). The groundwater system builds on the FlowLogo model by Castilla-Rho et al. (2015), which was then parameterized and calibrated with local hydrogeological inputs in Salar de Atacama, Chile. The social system of the ABM is defined and customozied based on empirical studies to reflect three major stressors: drought stress, population stress, and mining stress. The model reports evolution of groundwater changes and associated social stress dynamics within the modeled time frame.
This model illustrates actor interaction in the construction sector, according to information gathered in NL. It offers a simple frame to represent diverse interests, interdependencies and effects on the number of built sustainable houses.
This is a stylised agent-based model designed to explore the conditions that lead to lock-ins and transitions in agri-food systems.
The model represents interactions between four different types of agents: farmers, consumers, markets, and the state. Farmers and consumers are heterogeneous, and at each time step decide whether to trade with one of two market agents: the conventional or alternative. The state agent provides subsidies to the farmers at each time step.
The key emergent outcome is the fraction of trade in each time step that flows through the alternative market agent. This arises from the distributed decisions of farmer and consumer agents. A “sustainability transition” is defined as a shift in the dominant practices (and associated balance of power) towards the alternative paradigm.
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This paper investigates the impact of agents' trading decisions on market liquidity and transactional efficiency in markets for illiquid (hard-to-trade) assets. Drawing on a unique order book dataset from the fine wine exchange Liv-ex, we offer novel insights into liquidity dynamics in illiquid markets. Using an agent-based framework, we assess the adequacy of conventional liquidity measures in capturing market liquidity and transactional efficiency. Our main findings reveal that conventional liquidity measures, such as the number of bids, asks, new bids and new asks, may not accurately represent overall transactional efficiency. Instead, volume (measured by the number of trades) and relative spread measures may be more appropriate indicators of liquidity within the context of illiquid markets. Furthermore, our simulations demonstrate that a greater number of traders participating in the market correlates with an increased efficiency in trade execution, while wider trader-set margins may decrease the transactional efficiency. Interestingly, the trading period of the agents appears to have a significant impact on trade execution. This suggests that granting market participants additional time for trading (for example, through the support of automated trading systems) can enhance transactional efficiency within illiquid markets. These insights offer practical implications for market participants and policymakers aiming to optimise market functioning and liquidity.
ACT is an ABM based on an existing conceptualisation of the concept of critical transitions applied to the energy transition. With the model we departed from the mean-field approach simulated relevant actor behaviour in the energy transition.
The model studies the dynamics of risk-sharing cooperatives among heterogeneous farmers. Based on their knowledge on their risk exposure and the performance of the cooperative farmers choose whether or not to remain in the risk-sharing agreement.
Agriculture is the largest water-consuming sector worldwide, responsible for almost 70% of the world’s total freshwater consumption. Agricultural water reuse is one of the most sustainable and reliable methods to alleviate water shortages worldwide. However, the dynamics of agricultural water reuse adoption by farmers and its impacts on local water resources are still unknown to the scientific community, according to the literature. Therefore, the primary purpose of the WRAF model is to investigate the micro-level dynamics of agricultural water reuse adoption by farmers and its impacts on local water resources. The WRAF was developed using agent-based modeling as an exploratory tool for scenario analysis. The model was specifically designed for researchers and water resources decision-makers, especially those interested in natural resources management and water reuse.
WRAF simulates a virtual agricultural area in which several autonomous farms operate. It also simulates these farms’ water consumption dynamics. The developed model includes two types of agents: farmers and wastewater treatment plants. In general, farmer agents are the main water-consuming agents, and wastewater treatment plant agents are recycled water providers in the WRAF model. Dynamic simulation of agricultural water supply and demand in the area allows the user to observe the results of various irrigation water management scenarios, including recycled water. The models also enable the user to apply multiple climate change scenarios, including normal, moderate drought, severe drought, and wet weather conditions.
Displaying 10 of 64 results for "Stephanie Kramer-Schadt" clear search