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.
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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 1155 results for "Ian M Hamilton" clear search
A model of the emergence of intersectional life course inequalities through transitions in the workplace. It explores LGBTQ citizens’ career outcomes and trajectories in relation to several mediating factors: (i) workplace discrimination; (ii) social capital; (iii) policy interventions (i.e., workplace equality, diversity, and inclusion policies); (iv) and LGBTQ employees’ behaviours in response to discrimination (i.e., moving workplaces and/or different strategies for managing the visibility of their identity).
The “Descriptive Norm and Fraud Dynamics” model demonstrates how fraudulent behavior can either proliferate or be contained within non-hierarchical organizations, such as peer networks, through social influence taking the form of a descriptive norm. This model expands on the fraud triangle theory, which posits that an individual must concurrently possess a financial motive, perceive an opportunity, and hold a pro-fraud attitude to engage in fraudulent activities (red agent). In the absence of any of these elements, the individual will act honestly (green agent).
The model explores variations in a descriptive norm mechanism, ranging from local distorted knowledge to global perfect knowledge. In the case of local distorted knowledge, agents primarily rely on information from their first-degree colleagues. This knowledge is often distorted because agents are slow to update their empirical expectations, which are only partially revised after one-to-one interactions. On the other end of the spectrum, local perfect knowledge is achieved by incorporating a secondary source of information into the agents’ decision-making process. Here, accurate information provided by an observer is used to update empirical expectations.
The model shows that the same variation of the descriptive norm mechanism could lead to varying aggregate fraud levels across different fraud categories. Two empirically measured norm sensitivity distributions associated with different fraud categories can be selected into the model to see the different aggregate outcomes.
BESTMAP-ABM-DE is an agent-based model to determine the adoption and spatial allocation of selected agri-environmental schemes (AES) by individual farmers in the Mulde River Basin located in Western Saxony, Germany. The selected AES are buffer areas, cover crops, maintaining permanent grassland and conversion of arable land to permanent grassland. While the first three schemes have already been offered in the case study area, the latter scheme is a hypothetical scheme designed to test the impact of potential policy changes. For the first model analyses, only the currently offered schemes are considered. With the model, the effect of different scenarios of policy design on patterns of adoption can be investigated. In particular, the model can be used to study the social-ecological consequences of agricultural policies at different spatial and temporal scales and, in combination with biophysical models, test the ecological implications of different designs of the EU’s Common Agricultural Policy. The model was developed in the BESTMAP project.
An unintended consequence of low cost maritime travel may be hyperconnectedness, creating social situations where information can be readily passed before it is verified- an issue not limited to modern digitally connected societies. In traditional Coast Salish societies, the peoples of what is now Western Washington and Southwestern British Columbia, oral traditions were vertified through a process called witnessing. Witnesses would be trained to recount and verify oral history and traditional teachings at high fidelity. Here, a simple model based on dual inheritance approaches to genes and culture, is used to compare this specific form of verifying socially important information compared to modern mass communication. The model suggests that witnessing is a high fidelity form of transmitting knowledge with a low error rate, more in line with modern apprenticeships than mass communication. Social mechanisms such as witnessing provide solutions to issues faced in contemporary discourse where the validity of information and even fact checking mechanisms may be biased or counterfactual. This effort also demonstrates the utillity of using modeling approaches to highlight how specific, historically contingent institutions such as witnesses can be drawn upon to model potential solutions to contemporary issues solved in the past in traditional Coast Salish practice.
This model is designed to show the effects of personality types and student organizations have on ones chance to making friendships in a university setting. As known from psychology studies, those that are extroverted have an easier chance making friendships in comparison to those that are introverted.
Once every tick a pair of students (nodes) will be randomly selected they will then have the chance to either be come friends or not (create an edge or not) based on their personality type (you are able to change what the effect of each personality is) and whether or not they are in the same club (you can change this value) then the model triggers the next tick cycle to begin.
Spatial explicit model of a rangeland system, based on Australian conditions, where grass, woody shrubs and fire compete fore resources. Overgrazing can cause the system to flip from a healthy state to an unproductive shrub state. With the model one can explore the consequences of different movement rules of the livestock on the resilience of the system.
The model is discussed in Introduction to Agent-Based Modeling by Marco Janssen. For more information see https://intro2abm.com/.
To investigate the potential of using Social Psychology Theory in ABMs of natural resource use and show proof of concept, we present an exemplary agent-based modelling framework that explicitly represents multiple and hierarchical agent self-concepts
The impacts of income inequality can be seen everywhere, regardless of the country or the level of economic development. According to the literature review, income inequality has negative impacts in economic, social, and political variables. Notwithstanding of how well or not countries have done in reducing income inequality, none have been able to reduce it to a Gini Coefficient level of 0.2 or less.
This is the promise that a novel approach called Counterbalance Economics (CBE) provides without the need of increased taxes.
Based on the simulation, introducing the CBE into the Australian, UK, US, Swiss or German economies would result in an overall GDP increase of under 1% however, the level of inequality would be reduced from an average of 0.33 down to an average of 0.08. A detailed explanation of how to use the model, software, and data dependencies along with all other requirements have been included as part of the info tab in the model.
A model of attitudinal dynamics based on the cognitive mechanism of emotional coherence. The code is written in Java. For initialization an additional dataset is required.
The basic premise of the model is to simulate several ‘agents’ going through build-buy cycles: Build: Factories follow simple rules of strategy in the allocation of resources between making exploration and exploitation type products. Buy: Each of two types of Consumers, early-adopters and late adopters, follow simple purchase decision rules in deciding to purchase a product from one of two randomly chosen factories. Thus, the two working ‘agents’ of the model are ‘factories’ and […]
Displaying 10 of 1155 results for "Ian M Hamilton" clear search