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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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Models the connection between health agency communication, personal protective behaviour (eg vaccination, hand hygiene) and influenza transmission.
This is an agent-based model that simulates the structural evolution in food supply chain.
In the consumer advice network, users with connections can interact with each other, and the network topology will change during the opinion interaction. When the opinion distance from i to j is greater than the confidence threshold, the two consumers cannot exchange opinions, and the link between them will disconnect with probability DE. Then, a link from node i to node k is established with probability CE and node i learning opinion from node k.
This project is based on a Jupyter Notebook that describes the stepwise implementation of the EWA model in bi-matrix ( 2×2 ) strategic-form games for the simulation of economic learning processes. The output is a dataset with the simulated values of Attractions, Experience, selected strategies, and payoffs gained for the desired number of rounds and periods. The notebook also includes exploratory data analysis over the simulated output based on equilibrium, strategy frequencies, and payoffs.
The present model was created and used for the study titled ``Agent-Based Insight into Eco-Choices: Simulating the Fast Fashion Shift.” The model is implemented in the multi-agent programmable environment NetLogo 6.3.0. The model is designed to simulate the behavior and decision-making processes of individuals (agents) in a social network. It focuses on how agents interact with their peers, social media, and government campaigns, specifically regarding their likelihood to purchase fast fashion.
A group of agents share a resource and agents will become sufficiently motivated to adopt a rule to constraint their freedom if they experience resource scarcity and developed mutual trust relationships.
Exploring how learning and social-ecological networks influence management choice set and their ability to increase the likelihood of species coexistence (i.e. biodiversity) on a fragmented landscape controlled by different managers.
This model, realized on the NetLogo platform, compares utility levels at home and abroad to simulate agents’ migration and their eventual return. Our model is based on two fundamental individual features, i.e. risk aversion and initial expectation, which characterize the dynamics of different agents according to the evolution of their social contacts.
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.
We present an Agent-Based Stock Flow Consistent Multi-Country model of a Currency Union to analyze the impact of changes in the fiscal regimes that is permanent changes in the deficit-to-GDP targets that governments commit to comply.
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