Computational Model Library

Peer reviewed Dynamic Value-based Cognitive Architectures

Bart de Bruin | Published Tue Nov 30 20:29:58 2021

The intention of this model is to create an universal basis on how to model change in value prioritizations within social simulation. This model illustrates the designing of heterogeneous populations within agent-based social simulations by equipping agents with Dynamic Value-based Cognitive Architectures (DVCA-model). The DVCA-model uses the psychological theories on values by Schwartz (2012) and character traits by McCrae and Costa (2008) to create an unique trait- and value prioritization system for each individual. Furthermore, the DVCA-model simulates the impact of both social persuasion and life-events (e.g. information, experience) on the value systems of individuals by introducing the innovative concept of perception thermometers. Perception thermometers, controlled by the character traits, operate as buffers between the internal value prioritizations of agents and their external interactions. By introducing the concept of perception thermometers, the DVCA-model allows to study the dynamics of individual value prioritizations under a variety of internal and external perturbations over extensive time periods. Possible applications are the use of the DVCA-model within artificial sociality, opinion dynamics, social learning modelling, behavior selection algorithms and social-economic modelling.

Peer reviewed B3GET

Kristin Crouse | Published Thu Nov 14 20:07:16 2019 | Last modified Fri Dec 3 05:47:45 2021

B3GET simulates populations of virtual organisms evolving over generations, whose evolutionary outcomes reflect the selection pressures of their environment. The model simulates several factors considered important in biology, including life history trade-offs, investment in fighting ability and aggression, sperm competition, infanticide, and competition over access to food and mates. Downloaded materials include a starting genotype and population files. Edit the these files and see what changes occur in the behavior of virtual populations!

Modeling Personal Carbon Trading with ABM

Roman Seidl | Published Fri Dec 7 13:35:10 2018 | Last modified Thu Jul 29 07:52:21 2021

A simulated approach for Personal Carbon Trading, for figuring out what effects it might have if it will be implemented in the real world. We use an artificial population with some empirical data from international literature and basic assumptions about heterogeneous energy demand. The model is not to be used as simulating the actual behavior of real populations, but a toy model to test the effects of differences in various factors such as number of agents, energy price, price of allowances, etc. It is important to adapt the model for specific countries as carbon footprint and energy demand determines the relative success of PCT.

MCA-SdA (ABM of mining-community-aquifer interactions in Salar de Atacama, Chile)

Wenjuan Liu | Published Tue Dec 1 19:30:17 2020 | Last modified Thu Nov 4 18:10:42 2021

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.

Peer reviewed Virus Transmission with Super-spreaders

J Applegate | Published Sat Sep 11 05:14:27 2021

A curious aspect of the Covid-19 pandemic is the clustering of outbreaks. Evidence suggests that 80\% of people who contract the virus are infected by only 19% of infected individuals, and that the majority of infected individuals faile to infect another person. Thus, the dispersion of a contagion, $k$, may be of more use in understanding the spread of Covid-19 than the reproduction number, R0.

The Virus Transmission with Super-spreaders model, written in NetLogo, is an adaptation of the canonical Virus Transmission on a Network model and allows the exploration of various mitigation protocols such as testing and quarantines with both homogenous transmission and heterogenous transmission.

The model consists of a population of individuals arranged in a network, where both population and network degree are tunable. At the start of the simulation, a subset of the population is initially infected. As the model runs, infected individuals will infect neighboring susceptible individuals according to either homogenous or heterogenous transmission, where heterogenous transmission models super-spreaders. In this case, k is described as the percentage of super-spreaders in the population and the differing transmission rates for super-spreaders and non super-spreaders. Infected individuals either recover, at which point they become resistant to infection, or die. Testing regimes cause discovered infected individuals to quarantine for a period of time.

This model simulations social and childcare provision in the UK. Agents within simulated households can decide to provide for informal care, or pay for private care, for their loved ones after they have provided for childcare needs. Agents base these decisions on factors including their own health, employment status, financial resources, relationship to the individual in need and geographical location. This model extends our previous simulations of social care by simulating the impact of childcare demand on social care availability within households, which is known to be a significant constraint on informal care provision.

Results show that our model replicates realistic patterns of social and child care provision, suggesting that this framework can be a valuable aid to policy-making in this area.

Model of Rental Evictions in Phoenix During the Covid-19 Pandemic

Sean Bergin J Applegate | Published Sat Jul 31 17:39:59 2021 | Last modified Fri Oct 15 20:37:36 2021

The purpose of this model is to explore the dynamics of residency and eviction for households renting in the greater Phoenix (Arizona) metropolitan area. The model uses a representative population of renters modified from American Community Survey (ACS) data that includes demographic, housing and economic information. Each month, households pay their subsistence, rental and utility bills. If a household is unable to pay their monthly rent or utility bill they apply for financial assistance. This model provides a platform to understand the impact of various economic shock upon households. Also, the model includes conditions that occurred as a result of the Covid-19 pandemic which allows for the study of eviction mitigation strategies that were employed, such as the eviction moratorium and stimulus payments. The model allows us to make preliminary predictions concerning the number of households that may be evicted once the moratorium on evictions ends and the long-term effects on the number of evicted households in the greater Phoenix area going forward.

The purpose of this model is the simulation of social care provision in the UK, in which individual agents can decide to provide informal care, or pay for private care, for their loved ones. Agents base these decisions on factors including their own health, employment status, financial resources, relationship to the individual in need and geographical location. The model simulates care provision as a negotiation process conducted between agents across their kinship networks, with agents with stronger familial relationships to the recipient being more likely to attempt to allocate time to care provision. The model also simulates demographic change, the impact of socioeconomic status, and allows agents to relocate and change jobs or reduce working hours in order to provide care.
Despite the relative lack of empirical data in this model, the model is able to reproduce plausible patterns of social care provision. The inclusion of detailed economic and behavioural mechanisms allows this model to serve as a useful policy development tool; complex behavioural interventions can be implemented in simulation and tested on a virtual population before applying them in real-world contexts.

Pastoralscape

Matthew Sottile | Published Tue Oct 12 21:54:57 2021

Pastoralscape is a model of human agents, lifestock health and contageous disease for studying the impact of human decision making in pastoral communities within East Africa on livestock populations. It implements an event-driven agent based model in Python 3.

Network Behaviour Diffusion

Jennifer Badham | Published Sat Oct 2 22:44:08 2021

This model implements two types of network diffusion from an initial group of activated nodes. In complex contagion, a node is activated if the proportion of neighbour nodes that are already activated exceeds a given threshold. This is intended to represented the spread of health behaviours. In simple contagion, an activated node has a given probability of activating its inactive neighbours and re-tests each time step until all of the neighbours are activated. This is intended to represent information spread.

A range of networks are included with the model from secondary school friendship networks. The proportion of nodes initially activated and the method of selecting those nodes are controlled by the user.

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