This study separates operational interoperability, fare integration and revenue-sharing governance in a stylised multi-operator bus network. An agent-based model implemented in NetLogo 7.0.3 represents passengers, buses and stations across 14 stations, nine routes and three operators. A 2 × 2 institutional design is complemented by financial clearing comparisons and 43,200 robustness runs: behavioural sensitivity (E1), a 243-configuration operational factorial (E2), and targeted joint behavioural–operational stress testing (E3). The audited experiment records show favourable interoperability effects on waiting, total travel time, transfers and realised generalised cost in all 1,944 E2 and 768 E3 configuration-level primary comparisons. Fare integration substantially reduces passenger expenditure but produces an aggregate deficit under the assumed accounting coefficients. Revenue-sharing rules redistribute operator-level outcomes without changing aggregate profit or passenger trajectories by construction. The model is intended to identify mechanisms and test conditional robustness, not predict city-specific policy effects. The paper contributes an explicit separation of access, pricing and settlement mechanisms coupled with reproducible factorial and stress-test comparisons.

El modelo a continuación, fue desarrollado para el DATA CHALLENGE 2022. Es un análisis de la información descargada del Portal de datos abiertos de Ecuador. Dentro del modelo podemos realizar una breve exploración de la información así como una simulación respecto al proceso de vacunación en Ecuador.

According to the philosopher of science K. Popper “All life is problem solving”. Genetic algorithms aim to leverage Darwinian selection, a fundamental mechanism of biological evolution, so as to tackle various engineering challenges.
Flibs’NFarol is an Agent Based Model that embodies a genetic algorithm applied to the inherently ill-defined “El Farol Bar” problem. Within this context, a group of agents operates under bounded rationality conditions, giving rise to processes of self-organization involving, in the first place, efficiency in the exploitation of available resources. Over time, the attention of scholars has shifted to equity in resource distribution, as well. Nowadays, the problem is recognized as paradigmatic within studies of complex evolutionary systems.
Flibs’NFarol provides a platform to explore and evaluate factors influencing self-organized efficiency and fairness. The model represents agents as finite automata, known as “flibs,” and offers flexibility in modifying the number of internal flibs states, which directly affects their behaviour patterns and, ultimately, the diversity within populations and the complexity of the system.

This is a multi-patch meta-population ecological model. It intended as a test-bed in which to test the impact of humans with different kinds of social structure.

In this simulation, we modify the norms game model to bid-rigging (collusion) model, while we can simulate also the norms game model.

The purpose of this model is to analyze different configurations and scenarios of ecological corridors to simulate the movement of three avoider bird species at a local scale: Chondrohierax uncinatus (Accipitridae), a large carnivorous bird; Ampelion rubrocristatus (Cotingidae), a species that seeks areas with substantial land cover for refuge and rest; and Coeligena bonapartei (Trochilidae), a large hummingbird that prefers areas with a rich and diverse food supply. The model focusses on juvenile bird individuals seeking refuge and food, taking into account the mobility parameters of each species and the existing land cover types within the study area.
Specifically, the model aims to:
• Simulate the movement of 45 avoiders birds which are considered umbrella species sensitive to urban changes (which were chosen based on their specific biological and ecological requirements and parameters relevant to urban conservation efforts), 15 avoiders birds per specie to cross a two-dimensional world predominant urban.
• To be able to select which corridor scenario would be the most beneficial, in order to help the mobility of other species affected by urban fragmentation.
• Contribute to urban ecology research and support decision-making processes by relevant stakeholders.

REHAB has been designed as an ice-breaker in courses dealing with ecosystem management and participatory modelling. It helps introducing the two main tools used by the Companion Modelling approach, namely role-playing games and agent-based models.

This model was programmed for a class project, which studied the effects of urban sprawl on bird distribution. For the urban sprawl part of the model, we started from the model in (udhira, H. S., 200

Individually parameterized mussels (Mytilus californianus) recruit, grow, move and die in a 3D environment while facing predation (in the form of seastar agents), heat and desiccation with increased tide height, and storms. Parameterized with data collected by Wootton, Paine, Kandur, Donahue, Robles and others. See my 2019 CoMSES video presentation to learn more.

IOP 2.1.2 is an agent-based simulation model designed to explore the relations between (1) employees, (2) tasks and (3) resources in an organizational setting. By comparing alternative cognitive strategies in the use of resources, employees face increasingly demanding waves of tasks that derive by challenges the organization face to adapt to a turbulent environment. The assumption tested by this model is that a successful organizational adaptation, called plastic, is necessarily tied to how employees handle pressure coming from existing and new tasks. By comparing alternative cognitive strategies, connected to ‘docility’ (Simon, 1993; Secchi, 2011) and ‘extended’ cognition (Clark, 2003, Secchi & Cowley, 2018), IOP 2.1.2 is an attempt to indicate which strategy is most suitable and under which scenario.