Computational Model Library

Displaying 10 of 1066 results for "Oto Hudec" clear search

Aqua.MORE

Lisa Ambrosi Nico Bahro | Published Wednesday, November 20, 2019 | Last modified Saturday, July 03, 2021

Aqua.MORE (Agent-based MOdelling of REsources in Socio-Hydrological Systems) is an agent based modelling (ABM) approach to simulate the resource flow and social interaction in a coupled natural and social system of water supply and demand. The model is able to simulate the two-way feedback as socio-economic agents influence the natural resource flow and the availability of this resource influences the agents in their behaviour.

The model aims to investigate the role of Microfinance Institutes (MFIs) in strengthening the coping capacity of slum-dwellers (residents) in case of frequent disasters. The main purpose of the model is system understanding. It aids in understanding the following research question: Are the microcredits provided by MFI to start a small business helpful in increasing coping capacity of a slum dweller for recovering from frequent and intense disasters?

A model of the emergence of intersectional life course inequalities through transitions in the workplace. It explores LGBTQ citizens’ career outcomes and trajectories in relation to several mediating factors: (i) workplace discrimination; (ii) social capital; (iii) policy interventions (i.e., workplace equality, diversity, and inclusion policies); (iv) and LGBTQ employees’ behaviours in response to discrimination (i.e., moving workplaces and/or different strategies for managing the visibility of their identity).

Educational attainment and student retention in higher education are two of the main focuses of higher education research. Institutions in the U.S. are constantly looking for ways to identify areas of improvement across different aspects of the student experience on university campuses. This paper combines Department of Education data, U.S. Census data, and higher education theory on student retention, to build an agent-based model of student behavior.

02 OamLab V1.10 - Open Atwood Machine Laboratory

Garvin Boyle | Published Saturday, January 31, 2015 | Last modified Thursday, April 13, 2017

Using chains of replicas of Atwood’s Machine, this model explores implications of the Maximum Power Principle. It is one of a series of models exploring the dynamics of sustainable economics – PSoup, ModEco, EiLab, OamLab, MppLab, TpLab, EiLab.

The Palaeo-Agulhas Plain formed an important habitat exploited by Pleistocene hunter-gatherer populations during periods of lower sea level. This productive, grassy habitat would have supported numerous large-bodied ungulates accessible to a population of skilled hunters with the right hunting technology. It also provided a potentially rich location for plant food collection, and along its shores a coastline that moved with the rise and fall of sea levels. The rich archaeological and paleontological records of Pleistocene sites along the modern Cape south coast of South Africa, which would have overlooked the Palaeo-Agulhas Plain during Pleistocene times of lower sea level, provides a paleoarchive of this extinct ecosystem. In this paper, we present a first order illustration of the “palaeoscape modeling” approach advocated by Marean et al. (2015). We use a resourcescape model created from modern studies of habitat productivity without the Palaeo-Agulhas Plain. This is equivalent to predominant Holocene conditions. We then run an agent-based model of the human foraging system to investigate several research questions. Our agent-based approach uses the theoretical framework of optimal foraging theory to model human foraging decisions designed to optimize the net caloric gains within a complex landscape of spatially and temporally variable resources. We find that during the high sea-levels of MIS 5e (+5-6 m asl) and the Holocene, the absence of the Plain left a relatively poor food base supporting a much smaller population relying heavily on edible plant resources from the current Cape flora. Despite high species diversity of plants with edible storage organs, and marine invertebrates, encounter rates with highly profitable resources were low. We demonstrate that without the Palaeo-Agulhas Plain, human populations must have been small and low density, and exploited plant, mammal, and marine resources with relatively low caloric returns. The exposure and contraction of the Palaeo-Agulhas Plain was likely the single biggest driver of behavioral change during periods of climate change through the Pleistocene and into the transition to the Holocene.

Token Foraging in a Commons Dilemma

Nicholas Radtke | Published Monday, August 31, 2009 | Last modified Saturday, April 27, 2013

The model aims to mimic the observed behavior of participants in spatially explicit dynamic commons experiments.

Models the connection between health agency communication, personal protective behaviour (eg vaccination, hand hygiene) and influenza transmission.

In the consumer advice network, users with connections can interact with each other, and the network topology will change during the opinion interaction. When the opinion distance from i to j is greater than the confidence threshold, the two consumers cannot exchange opinions, and the link between them will disconnect with probability DE. Then, a link from node i to node k is established with probability CE and node i learning opinion from node k.

Peer reviewed lgm_ecodynamics

Colin Wren | Published Monday, April 22, 2019

This is a modification of a model published previous by Barton and Riel-Salvatore (2012). In this model, we simulate six regional populations within Last Glacial Maximum western Europe. Agents interact through reproduction and genetic markers attached to each of six regions mix through subsequent generations as a way to track population dynamics, mobility, and gene flow. In addition, the landscape is heterogeneous and affects agent mobility and, under certain scenarios, their odds of survival.

Displaying 10 of 1066 results for "Oto Hudec" clear search

This website uses cookies and Google Analytics to help us track user engagement and improve our site. If you'd like to know more information about what data we collect and why, please see our data privacy policy. If you continue to use this site, you consent to our use of cookies.
Accept