This model represnts an unique human-aquifer interactions model for the Li-extraction in Salar de Atacama, Chile. It describes the local actors’ experience of mining-induced changes in the socio-ecological system, especially on groundwater changes and social stressors. Social interactions are designed specifically according to a long-term local fieldwork by Babidge et al. (2019, 2020). The groundwater system builds on the FlowLogo model by Castilla-Rho et al. (2015), which was then parameterized and calibrated with local hydrogeological inputs in Salar de Atacama, Chile. The social system of the ABM is defined and customozied based on empirical studies to reflect three major stressors: drought stress, population stress, and mining stress. The model reports evolution of groundwater changes and associated social stress dynamics within the modeled time frame.

A very simple model elaborated to explore what may happens when buyers (travelers) have more information than sellers (tourist destinations)

The simulation model SimPLS shows an application of the PLS agent concept, using SEM as empirical basis for the definition of agent architectures. The simulation model implements the PLS path model TAM about the decision of using innovative products.

This is a NetLogo version of Buhl et al.’s (2005) model of self-organised digging activity in ant colonies. It was built for a master’s course on self-organisation and its intended use is still educational. The ants’ behavior can easily be changed by toggling switches on the interface, or, for more advanced students, there is R code included allowing the model to be run and analysed through RNetLogo.

We model interpersonal dynamics and study behavior in the classroom in the hypothetical case of a single teacher who defines students’ seating arrangements. The model incorporates the mechanisms of peer influence on study behavior, on attitude formation, and homophilous selection in order to depict the interrelated dynamics of networks, behavior, and attitudes. We compare various seating arrangement scenarios and observe how GPA distribution and level of prejudice changes over time.

This is a conceptual model of underlying forces creating industrial clusters. There are two contradictory forces - attraction and repulsion. Firms within the same Industry are attracted to each other and on the other hand, firms with the same Activity are repulsed from each other. In each round firm with the lowest fitness is selected to change its profile of Industries and Activities. Based on these simple rules interesting patterns emerge.

Educational attainment and student retention in higher education are two of the main focuses of higher education research. Institutions in the U.S. are constantly looking for ways to identify areas of improvement across different aspects of the student experience on university campuses. This paper combines Department of Education data, U.S. Census data, and higher education theory on student retention, to build an agent-based model of student behavior.

GFN & Technology Models Library (2025–2035) is a collection of four interrelated computational models focused on global financial networks, cascading default risks, technological development, and technological lag, with particular attention to Russia, the USA, and China. The library combines agent-based modeling, system dynamics, Monte-Carlo simulation, and network analysis. It includes: (1) a Numba-accelerated Monte-Carlo technology index model; (2) a hybrid GFN + cascading defaults (Gai–Kapadia) + Russian system dynamics model; (3) a twin-simulation GFN+SBS framework with selective bailout and Russia’s peripheral position; and (4) an endogenous GFN model with technology centrality, dependence, and tech lag dynamics under sanctions scenarios. GFN & Technology Models Library (2025–2035) is a collection of four interrelated computational models focused on global financial networks, cascading default risks, technological development, and technological lag, with particular attention to Russia, the USA, and China.

The library combines agent-based modeling, system dynamics, Monte-Carlo simulation, and network analysis. It includes:

1. Technology Index 2035 (Monte-Carlo + Numba) — hybrid SD/ABM model projecting a composite technology index under different scenarios (Russia baseline, China, USA) with aggressive Numba optimization.
2. RUS-GFN-TSI-2035 CASCADE — hybrid model integrating a Gai–Kapadia-style cascading defaults network, an agent-based Global Financial Network layer, and a system-dynamics module for the Russian economy (TSI, inflation, technology, trust, etc.).
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Modified SKIN Model based on absorptive capacity concept.

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.