The Urban Traffic Simulator is an agent-based model developed in the Unity platform. The model allows the user to simulate several autonomous vehicles (AVs) and tune granular parameters such as vehicle downforce, adherence to speed limits, top speed in mph and mass. The model allows researchers to tune these parameters, run the simulator for a given period and export data from the model for analysis (an example is provided in Jupyter Notebook).

The data the model is currently able to output are the following:

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LogoClim is a NetLogo model designed to be integrated into other simulations through the LevelSpace extension (Hjorth et al., 2020), providing high resolution climate data from sources validated and used by the Intergovernmental Panel on Climate Change (IPCC).

The model simplifies and standardizes the integration of climate data into NetLogo, allowing researchers to focus their efforts on the model itself with the assurance of using reliable and widely recognized data. Although its main use is as a component of larger simulations, LogoClim also has its own graphical interface for monitoring and checking the datasets.

The climate data comes from the WorldClim 2.1 project (Fick & Hijmans, 2017), for which LogoClim works as an interface to NetLogo. The model supports all three WorldClim data series: (1) Historical Climate Data (1970 to 2000), with 12 monthly points for minimum, mean, and maximum temperature, precipitation, solar radiation, wind speed, vapor pressure, elevation, and bioclimatic variables; (2) Historical Monthly Weather Data (1951 to 2024), based on downscaling of CRU-TS-4.09, developed by the Climatic Research Unit at the University of East Anglia (Harris et al., 2020), with minimum and maximum temperature and total precipitation; and (3) Future Climate Data, based on downscaling climate projections derived from global climate models of the Coupled Model Intercomparison Project Phase 6 (CMIP6) (Eyring et al., 2016) for four future periods (2021 to 2040, 2041 to 2060, 2061 to 2080, and 2081 to 2100) and four scenarios based on the Shared Socioeconomic Pathways (SSPs 126, 245, 370, and 585), covering minimum and maximum temperature, total precipitation, and bioclimatic variables. All series are available at multiple spatial resolutions, from 10 minutes (about 340 km² at the equator) to 30 seconds (about 1 km² at the equator).

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Inspired by the SKIN model, the basic concept here is to model the acceptance and implementation of supplier innovations. This model includes three types of agents comprising suppliers, manufacturers and applicators.

Disparities in access to primary health care have led to health disadvantages among Latinos and other non-White racial groups. To better identify and understand which policies are most likely to improve health care for Latinos, we examined differences in access to primary care between Latinos with proficient English language skills and Latinos with limited English proficiency (LEP) and estimated the extent of access to primary care providers (PCPs) among Latinos in the U.S.

Within the archeological record for Bronze Age Chinese culture, there continues to be a gap in our understanding of the sudden rise of the Erlitou State from the previous late Longshan chiefdoms. In order to examine this period, I developed and used an agent-based model (ABM) to explore possible socio-politically relevant hypotheses for the gap between the demise of the late Longshan cultures and rise of the first state level society in East Asia. I tested land use strategy making and collective action in response to drought and flooding scenarios, the two plausible environmental hazards at that time. The model results show cases of emergent behavior where an increase in social complexity could have been experienced if a catastrophic event occurred while the population was sufficiently prepared for a different catastrophe, suggesting a plausible lead for future research into determining the life of the time period.

The ABM published here was originally developed in 2016 and its results published in the Proceedings of the 2017 Winter Simulation Conference.

3spire is an ABM where farming households make management decisions aimed at satisficing along the aspirational dimensions: food self-sufficiency, income, and leisure. Households decision outcomes depend on their social networks, knowledge, assets, household needs, past management, and climate/market trends

AMIRIS is the Agent-based Market model for the Investigation of Renewable and Integrated energy Systems.

It is an agent-based simulation of electricity markets and their actors.
AMIRIS enables researches to analyse and evaluate energy policy instruments and their impact on the actors involved in the simulation context.
Different prototypical agents on the electricity market interact with each other, each employing complex decision strategies.
AMIRIS allows to calculate the impact of policy instruments on economic performance of power plant operators and marketers.
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The model measures drivers of effectiveness of risk assessments in risk workshops regarding the correctness and required time. Specifically, we model the limits to information transfer, incomplete discussions, group characteristics, and interaction patterns and investigate their effect on risk assessment in risk workshops.

The model simulates a discussion in the context of a risk workshop with 9 participants. The participants use Bayesian networks to assess a given risk individually and as a group.

The purpose of the model is to better understand, how different factors for human residential choices affect the city’s segregation pattern. Therefore, a Schelling (1971) model was extended to include ethnicity, income, and affordability and applied to the city of Salzburg. So far, only a few studies have tried to explore the effect of multiple factors on the residential pattern (Sahasranaman & Jensen, 2016, 2018; Yin, 2009). Thereby, models using multiple factors can produce more realistic results (Benenson et al., 2002). This model and the corresponding thesis aim to fill that gap.

An agent-based model simulating West Nile Virus dynamics in a one host (American robin)-one vector (Culex spp. mosquito) system. ODD improved and code cleaned.