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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.
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Chicago’s demographic, neighborhood, sex risk behaviors, sexual network data, and HIV prevention and treatment cascade information from 2015 were integrated as input to a new agent-based model (ABM) called the Levers-of-HIV-Model (LHM). This LHM, written in NetLogo, forms patterns of sexual relations among Men who have Sex with Men (MSM) based on static traits (race/ethnicity, and age) and dynamic states (sexual relations and practices) that are found in Chicago. LHM’s five modules simulate and count new infections at the two marker years of 2023 and 2030 for a wide range of distinct scenarios or levers, in which the levels of PrEP and ART linkage to care, retention, and adherence or viral load are increased over time from the 2015 baseline levels.
This is an implementation of an agent based model for the evolution of ethnocentrism. While based off a model published by Hammond and Axelrod (2006), the code has been modified to allow for a more fine-grained analysis of evolutionary dynamics.
Simulation to replicate and extend an analytical model (Konrad & Skaperdas, 2010) of the provision of security as a collective good. We simulate bandits preying upon peasants in an anarchy condition.
The simulation generates two kinds of agents, whose proposals are generated accordingly to their selfish or selfless behaviour. Then, agents compete in order to increase their portfolio playing the ultimatum game with a random-stranger matching.
This study investigates a possible nexus between inter-group competition and intra-group cooperation, which may be called “tribalism.” Building upon previous studies demonstrating a relationship between the environment and social relations, the present research incorporates a social-ecological model as a mediating factor connecting both individuals and communities to the environment. Cyclical and non-cyclical fluctuation in a simple, two-resource ecology drive agents to adopt either “go-it-alone” or group-based survival strategies via evolutionary selection. Novelly, this simulation employs a multilevel selection model allowing group-level dynamics to exert downward selective pressures on individuals’ propensity to cooperate within groups. Results suggest that cooperation and inter-group conflict are co-evolved in a triadic relationship with the environment. Resource scarcity increases inter-group competition, especially when resources are clustered as opposed to widely distributed. Moreover, the tactical advantage of cooperation in the securing of clustered resources enhanced selective pressure on cooperation, even if that implies increased individual mortality for the most altruistic warriors. Troubling, these results suggest that extreme weather, possibly as a result of climate change, could exacerbate conflict in sensitive, weather-dependent social-ecologies—especially places like the Horn of Africa where ecologically sensitive economic modalities overlap with high-levels of diversity and the wide-availability of small arms. As well, global development and foreign aid strategists should consider how plans may increase the value of particular locations where community resources are built or aid is distributed, potentially instigating tribal conflict. In sum, these factors, interacting with pre-existing social dynamics dynamics, may heighten inter-ethnic or tribal conflict in pluralistic but otherwise peaceful communities.
For special issue submission in JASSS.
DARTS simulates food systems in which agents produce, consume and trade food. Here, food is a summary item that roughly corresponds to commodity food types (e.g. rice). No other food types are taken into account. Each food system (World) consists of its own distribution of agents, regions and connections between agents. Agents differ in their ability to produce food, earn off-farm income and trade food. The agents aim to satisfy their food requirements (which are fixed and equal across agents) by either their own food production or by food purchases. Each simulation step represents one month, in which agents can produce (if they have productive capacity and it is a harvest month for their region), earn off-farm income, trade food (both buy and sell) and consume food. We evaluate the performance of the food system by averaging the agents’ food satisfaction, which is defined as the ratio of the food consumed by each agent at the end of each month divided by her food requirement. At each step, any of the abovementioned attributes related to the agents’ ability to satisfy their food requirement can (temporarily) be shocked. These shocks include reducing the amount of food they produce, removing their ability to trade locally or internationally and reducing their cash savings. Food satisfaction is quantified (both immediately after the shock and in the year following the shock) to evaluate food security of a particular food system, both at the level of agent types (e.g. the urban poor and the rural poor) and at the systems level. Thus, the effects of shocks on food security can be related to the food system’s structure.
This model simulates a foraging system based on Middle Stone Age plant and shellfish foraging in South Africa.
A general model of human mate choice in which agents are localized in space, interact with close neighbors, and tend to range either near or far. At the individual level, our model uses two oft-used but incompletely understood decision rules: one based on preferences for similar partners, the other for maximally attractive partners.
This model is to simulate and compare the admission effects of 3 school matching mechanisms, serial dictatorship, Boston mechanism, and Chinese Parallel, under different settings of information released.
The purpose of this model is to examine equity and efficiency in crop production across a system of irrigated farms, as a function of maintenance costs, assessed water fees, and the capacity of farmers to trade water rights among themselves.
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