Computational Model Library

Displaying 10 of 1143 results for "Lee-Ann Sutherland" clear search

Agent-Based Computational Model of the cryptocurrency Bitcoin with a realistic market and transaction system. Bitcoin’s transaction limit (i.e. block size) and Bitcoin generation can be calibrated and optimized for wealth and network’s hashing power by the Non-Dominated Sorted Genetic Algorithm - II.

Diffusion dynamics in small-world networks with heterogeneous consumers

Sebastiano Delre | Published Saturday, September 10, 2011 | Last modified Saturday, April 27, 2013

This model simulates diffusion curves and it allows to test how social influence, network structure and consumer heterogeneity affect their spreads and their speeds.

Agent-based model for centralized student admission process

Connie Wang Shu-Heng Chen Bin-Tzong Chi | Published Wednesday, November 04, 2015 | Last modified Wednesday, March 06, 2019

This model is to match students and schools using real-world student admission mechanisms. The mechanisms in this model are serial dictatorship, deferred acceptance, the Boston mechanism, Chinese Parallel, and the Taipei mechanism.

We expose RA agent-based model of the opinion and tolerance dynamics in artificial societies. The formal mathematical model is based on the ideas of Social Influence, Social Judgment, and Social Identity theories.

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.

Double Auction

Timothy Gooding | Published Sunday, February 24, 2019

This model reproduces the double auction experiments and explores the difference between short-term and long-term trading and pricing.

The model explores the impact of public disclosure on tax compliance among diverse agents, including individual taxpayers and a tax authority. It incorporates heterogeneous preferences and income endowments among taxpayers, captured through a utility function that considers psychic costs subtracted from expected pecuniary utility. These costs include moral, reciprocity, and stigma costs associated with norm violations, leading to variations in taxpayers’ risk attitudes and related parameters. The tax authority’s attributes, such as the frequency of random audits, penalty rate, and the choice between partial or full disclosure, remain fixed throughout the simulation. Income endowments and preference parameters are randomly assigned to taxpayers at the outset.

Taxpayers maximize their expected utility by reporting income, taking into account tax, penalty, and audit rates. They make annual decisions based on their own and their peers’ behaviors from the previous year. Taxpayers indirectly interact at the societal level through public disclosure conducted by the tax authority, exchanging tax information among peers. Each period in the simulation collects data on total reported income, average compliance rates per income group, distribution of compliance rates, counts of compliers, full evaders, partial evaders, and the numbers of taxpayers experiencing guilt and anger. The model evaluates whether public disclosure positively or negatively impacts compliance rates and quantifies this impact based on aggregated individual reporting behaviors.

Spatial model of the noisy Prisoner's Dilemma with reward shift

Matus Halas | Published Thursday, March 05, 2015 | Last modified Tuesday, May 29, 2018

Interactions of players embedded in a closed square lattice are determined by distance and overall gains and they lead to shifts of reward payoff between temptation and punishment. A new winner balancing against threats is ultimately discovered.

Peer reviewed Lethal Geometry

Kristin Crouse | Published Friday, February 21, 2020 | Last modified Wednesday, December 15, 2021

LethalGeometry was developed to examine whether territory size influences the mortality risk for individuals within that territory. For animals who live in territoral groups and are lethally aggressive, we can expect that most aggression occurs along the periphery (or border) between two adjacent territories. For territories that are relatively large, the periphery makes up a proportionately small amount of the of the total territory size, suggesting that individuals in these territories might be less likely to die from these territorial skirmishes. LethalGeometry examines this geometric relationship between territory size and mortality risk under realistic assumptions of variable territory size and shape, variable border width, and stochastic interactions and movement.

The individuals (agents) are programmed to walk randomly about their environment, search for and eat food to obtain energy, reproduce if they can, and act aggressively toward individuals of other groups. During each simulation step, individuals analyze their environment and internal state to determine which actions to take. The actions available to individuals include moving, fighting, and giving birth.

Feedback Loop Example: Forest Resource Transport

James Millington | Published Friday, December 21, 2012 | Last modified Saturday, April 27, 2013

This model illustrates a positive ‘transport’ feedback loop in which lines with different resistance to flows of material result in variation in rates of change in linked entities.

Displaying 10 of 1143 results for "Lee-Ann Sutherland" clear search

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