Computational Model Library

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:

Peer reviewed Evolution of Ecological Communities: Testing Constraint Closure

Steve Peck | Published Sun Dec 6 19:37:54 2020 | Last modified Fri Apr 16 22:17:46 2021

Ecosystems are among the most complex structures studied. They comprise elements that seem both stable and contingent. The stability of these systems depends on interactions among their evolutionary history, including the accidents of organisms moving through the landscape and microhabitats of the earth, and the biotic and abiotic conditions in which they occur. When ecosystems are stable, how is that achieved? Here we look at ecosystem stability through a computer simulation model that suggests that it may depend on what constrains the system and how those constraints are structured. Specifically, if the constraints found in an ecological community form a closed loop, that allows particular kinds of feedback may give structure to the ecosystem processes for a period of time. In this simulation model, we look at how evolutionary forces act in such a way these closed constraint loops may form. This may explain some kinds of ecosystem stability. This work will also be valuable to ecological theorists in understanding general ideas of stability in such systems.

The purpose of the model is to explore the influence of two circular business models (CBMs), i.e. Circular Waste Management and Waste-as-byproduct, and its design variables on CBM viability. The model represents an Industrial Symbiosis Network (ISN) in which a processor uses the organic waste from suppliers to produce biogas and nutrient rich digestate for local reuse. The model can be used to test the viability of the CBM, which is expressed as value captured (avg. cash flow/ton waste/actor) and the survival of the network over time.

In the model, the value captured is calculated relative to the initial state, using incineration costs as a benchmark. Moderating variables are interactions with the waste incinerator and actor behaviour factors. Actors may leave the network when the waste supply for local production is too low, or when personal economic benefits are too low. When the processor decides to leave, the network fails.

This is a variant of the PaleoscapeABM model available here written by Wren and Janssen. In this variant, we give projectile weapons to hunter and document where they discard them over time. Discard rate and location are influenced by probabilities of hitting/missing the prey, probabilities of damaging the weapon, and probabilities of carrying back embedded projectile armatures to the habitation camp with the body carcass.

The Netlogo model is a conceptualization of the Moria refugee camp, capturing the household demographics of refugees in the camp, a theoretical friendship network based on values, and an abstraction of their daily activities. The model then simulates how Covid-19 could spread through the camp if one refugee is exposed to the virus, utilizing transmission probabilities and the stages of disease progression of Covid-19 from susceptible to exposed to asymptomatic / symptomatic to mild / severe to recovered from literature. The model also incorporates various interventions - PPE, lockdown, isolation of symptomatic refugees - to analyze how they could mitigate the spread of the virus through the camp.

The simulation is a variant of the “ToRealSim OD variants - base v2.7” base model, which is based on the standard DW opinion dynamics model (but with the differences that rather than one agent per tick randomly influencing another, all agents randomly influence one other per tick - this seems to make no difference to the outcomes other than to scale simulation time). Influence can be made one-way by turning off the two-way? switch

Various additional variations and sources of noise are possible to test robustness of outcomes to these (compared to DW model).
In this version agent opinions change following the empirical data collected in some experiments (Takács et al 2016).

Such an algorithm leaves no role for the uncertainties in other OD models. [Indeed the data from (Takács et al 2016) indicates that there can be influence even when opinion differences are large - which violates a core assumption of these]. However to allow better comparison with other such models there is a with-un? switch which allows uncertainties to come into play. If this is on, then influence (according to above algorithm) is only calculated if the opinion difference is less than the uncertainty. If an agent is influenced uncertainties are modified in the same way as standard DW models.

Bicycle model

Dana Kaziyeva Gudrun Wallentin Martin Loidl | Published Thu Jan 10 21:30:34 2019 | Last modified Mon Feb 22 14:32:32 2021

The purpose of the model is to generate the spatio-temporal distribution of bicycle traffic flows at a regional scale level. Disaggregated results are computed for each network segment with the minute time step. The human decision-making is governed by probabilistic rules derived from the mobility survey.

Peer reviewed Evolution of Sex

Kristin Crouse | Published Sun Jun 5 08:24:01 2016 | Last modified Mon Feb 15 15:40:39 2021

Evolution of Sex is a NetLogo model that illustrates the advantages and disadvantages of sexual and asexual reproductive strategies. It seeks to demonstrate the answer to the question “Why do we have sex?”

In recent years we have seen multiple incidents with a large number of people injured and killed by one or more armed attackers. Since this type of violence is difficult to predict, detecting threats as early as possible allows to generate early warnings and reduce response time. In this context, any tool to check and compare different action protocols can be a further step in the direction of saving lives. Our proposal combines features from continuous and discrete models to obtain the best of both worlds in order to simulate large and crowded spaces where complex behavior individuals interact. With this proposal we aim to provide a tool for testing different security protocols under several emergency scenarios, where spaces, hazards, and population can be customized. Finally, we use a proof of concept implementation of this model to test specific security protocols under emergency situations for real spaces. Specifically, we test how providing some users of a university college with an app that informs about the type and characteristics of the ongoing hazard, affects in the safety performance.

The SimPioN model aims to abstractly reproduce and experiment with the conditions under which a path-dependent process may lead to a (structural) network lock-in in interorganisational networks.

Path dependence theory is constructed around a process argumentation regarding three main elements: a situation of (at least) initially non-ergodic (unpredictable with regard to outcome) starting conditions in a social setting; these become reinforced by the workings of (at least) one positive feedback mechanism that increasingly reduces the scope of conceivable alternative choices; and that process finally results in a situation of lock-in, where any alternatives outside the already adopted options become essentially impossible or too costly to pursue despite (ostensibly) better options theoretically being available.

The purpose of SimPioN is to advance our understanding of lock-ins arising in interorganisational networks based on the network dynamics involving the mechanism of social capital. This mechanism and the lock-ins it may drive have been shown above to produce problematic consequences for firms in terms of a loss of organisational autonomy and strategic flexibility, especially in high-tech knowledge-intensive industries that rely heavily on network organising.

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