Computational Model Library

Displaying 10 of 199 results for 'G M Leighton'

LimnoSES - social-ecological lake management undergoing regime shifts

Romina Martin | Published Thursday, November 24, 2016 | Last modified Friday, January 18, 2019

LimnoSES is a coupled system dynamics, agent-based model to simulate social-ecological feedbacks in shallow lake use and management.

We compare three model estimates for the time and treatment requirements to eliminate HCV among HIV-positive MSM in Victoria, Australia: a compartmental model; an ABM parametrized by surveillance data; and an ABM with a more heterogeneous population.

This model aims to investigate how different type of learning (social system) and disturbance specific attributes (ecological system) influence adoption of treatment strategies to treat the effects of ecological disturbances.

Peer reviewed Emergent Firms Model

J Applegate | Published Friday, July 13, 2018

The Emergent Firm (EF) model is based on the premise that firms arise out of individuals choosing to work together to advantage themselves of the benefits of returns-to-scale and coordination. The Emergent Firm (EF) model is a new implementation and extension of Rob Axtell’s Endogenous Dynamics of Multi-Agent Firms model. Like the Axtell model, the EF model describes how economies, composed of firms, form and evolve out of the utility maximizing activity on the part of individual agents. The EF model includes a cash-in-advance constraint on agents changing employment, as well as a universal credit-creating lender to explore how costs and access to capital affect the emergent economy and its macroeconomic characteristics such as firm size distributions, wealth, debt, wages and productivity.

We propose an agent-based model where a fixed finite population of tagged agents play iteratively the Nash demand game in a regular lattice. The model extends the bargaining model by Axtell, Epstein and Young.

Transport simulation in a real road network

Jiaqi Ge Gary Polhill | Published Tuesday, April 17, 2018 | Last modified Tuesday, April 17, 2018

Ge, J., & Polhill, G. (2016). Exploring the Combined Impact of Factors Influencing Commuting Patterns and CO2 Emission in Aberdeen Using an Agent-Based Model. Journal of Artificial Societies and Social Simulation, 19(3). http://jasss.soc.surrey.ac.uk/19/3/11.html
We develop an agent-based transport model using a realistic GIS-enabled road network and the car following method. The model can be used to study the impact of social interventions such as flexi-time and workplace sharing, as well as large infrastructure such as the construction of a bypass or highway. The model is developed in Netlogo version 5 and requires road network data in GIS format to run.

The model represents empirically observed recycling behaviour of Chinese citizens, based on the theory of reasoned action (TRA), the theory of planned behaviour (TPB) and the theory of planned behaviour extended with situational factors (TPB+).

A model on feeding and social interaction behaviour of pigs

Iris J.M.M. Boumans | Published Thursday, May 04, 2017 | Last modified Tuesday, February 27, 2018

The model simulates interaction between internal physiological factors (e.g. energy balance) and external social factors (e.g. competition level) underlying feeding and social interaction behaviour of commercially group-housed pigs.

Last Mile Commuter Behavior Model

Moira Zellner Dean Massey Yoram Shiftan Jonathan Levine Maria Arquero | Published Friday, November 07, 2014 | Last modified Friday, November 07, 2014

We represent commuters and their preferences for transportation cost, time and safety. Agents assess their options via their preferences, their environment, and the modes available. The model has policy levers to test impact on last-mile problem.

CoDMER v. 2.0 was parameterized with ethnographic data from organizations dealing with prescribed fire and seeding native plants, to advance theory on how collective decisions emerge in ecological restoration.

Displaying 10 of 199 results for 'G M Leighton'

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