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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.
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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.
The objective of this study is to create a framework to simulate and analyze the effect of multiple business scenarios on the adoption behavior of a group of technology products.
CRESY-I stands for CREativity from a SYstems perspetive, Model I. This is the base model in a series designed to describe a systems approach to creativity in terms of variation, selection and retention (VSR) subprocesses.
The model simulates interactions in small, task focused groups that might lead to the emergence of status beliefs among group members.
Previous work with the spatial iterated prisoner’s dilemma has shown that “walk away” cooperators are able to outcompete defectors as well as cooperators that do not respond to defection, but it remains to be seen just how robust the so-called walk away strategy is to ecologically important variables such as population density, error, and offspring dispersal. Our simulation experiments identify socio-ecological conditions in which natural selection favors strategies that emphasize forgiveness over flight in the spatial iterated prisoner’s dilemma. Our interesting results are best explained by considering how population density, error, and offspring dispersal affect the opportunity cost associated with walking away from an error-prone partner.
Aroused public opinion has led to public debates on social responsibility issues in food supply chains. This model based op opinion dynamics and the linkages between involved actors simulates the public debate leading to the transitions.
This model accompanies a paper looking at the role and limits of values and norms for modeling realistic social agents. Based on literature we synthesize a theory on norms and a theory that combines both values and norms. In contrast to previous work, these theories are checked against data on human behavior obtained from a psychological experiment on dividing money: the ultimatum game. We found that agents that act according to a theory that combines both values and norms, produce behavior quite similar to that of humans. Furthermore, we found that this theory is more realistic than theories solely concerned with norms or theories solely concerned with values. However, to explain the amount of money people accept in this ultimatum game we will eventually need an even more realistic theory. We propose that a theory that explains when people exactly choose to use norms instead of values could provide this realism.
The model represents a set of social actors engaged into a collegiate (composed of representants of civil society and public sector) to manage the Southern Rural Territory of Sergipe (SRTS), created by two territorial public policies, the National Program for the Sustainable Development of Rural Territories (PRONAT) and the Program Territories of Citizenship (PTC) which aim at balancing power relations between social actors of Rural Territories. The main gola of these public policies is to empower the civil society engaged in the territory to enable them to negotiate with the traditional power (mainly majors). It was designed two models of the SRTS, one that represents the situation in 2012, and other that represents the social interdependencies in 2017. For each period it is possible to measure the capability and power of each modeled social actor and see whether it is observed the empowerment of the civil society or not.
This BNE-informed ABM ultimately aims to provide a more realistic description of complicated pedestrian behaviours especially in high-density and life-threatening situations. Bayesian Nash Equilibrium (BNE) was adopted to reproduce interactive decision-making process among rational and game-playing agents. The implementations of 3 behavioural models, which are Shortest Route (SR) model, Random Follow (RF) model, and BNE model, make it possible to simulate emergent patterns of pedestrian behaviours (e.g. herding and self-organised queuing behaviours, etc.) in emergency situations.
According to the common features of previous mass trampling accidents, a series of simulation experiments were performed in space with 3 types of barriers, which are Horizontal Corridors, Vertical Corridors, and Random Squares, standing for corridors, bottlenecks and intersections respectively, to investigate emergent behaviours of evacuees in varied constricted spatial environments. The output of this ABM has been available at https://data.mendeley.com/datasets/9v4byyvgxh/1.
A logging agent builds roads based on the location of high-value hotspots, and cuts trees based on road access. A forest monitor sanctions the logger on observed infractions, reshaping the pattern of road development.
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