Computational Model Library

Displaying 10 of 963 results for "J Van Der Beek" clear search

This model implements a classic scenario used in Reinforcement Learning problem, the “Cliff Walking Problem”. Consider the gridworld shown below (SUTTON; BARTO, 2018). This is a standard undiscounted, episodic task, with start and goal states, and the usual actions causing movement up, down, right, and left. Reward is -1 on all transitions except those into the region marked “The Cliff.” Stepping into this region incurs a reward of -100 and sends the agent instantly back to the start (SUTTON; BARTO, 2018).

CliffWalking

The problem is solved in this model using the Q-Learning algorithm. The algorithm is implemented with the support of the NetLogo Q-Learning Extension

Interactions between organizations and social networks in common-pool resource governance

Phesi Project | Published Monday, October 29, 2012 | Last modified Saturday, April 27, 2013

Explores how social networks affect implementation of institutional rules in a common pool resource.

Frotembo

Christophe Le Page Kadiri Serge Bobo | Published Thursday, October 16, 2014

A stylized scale model to codesign with villagers an agent-based model of bushmeat hunting in the periphery of Korup National Park (Cameroon)

WATER REUSE ADOPTION BY FARMERS (WRAF)

Farshid Shoushtarian | Published Tuesday, September 27, 2022

Agriculture is the largest water-consuming sector worldwide, responsible for almost 70% of the world’s total freshwater consumption. Agricultural water reuse is one of the most sustainable and reliable methods to alleviate water shortages worldwide. However, the dynamics of agricultural water reuse adoption by farmers and its impacts on local water resources are still unknown to the scientific community, according to the literature. Therefore, the primary purpose of the WRAF model is to investigate the micro-level dynamics of agricultural water reuse adoption by farmers and its impacts on local water resources. The WRAF was developed using agent-based modeling as an exploratory tool for scenario analysis. The model was specifically designed for researchers and water resources decision-makers, especially those interested in natural resources management and water reuse.
WRAF simulates a virtual agricultural area in which several autonomous farms operate. It also simulates these farms’ water consumption dynamics. The developed model includes two types of agents: farmers and wastewater treatment plants. In general, farmer agents are the main water-consuming agents, and wastewater treatment plant agents are recycled water providers in the WRAF model. Dynamic simulation of agricultural water supply and demand in the area allows the user to observe the results of various irrigation water management scenarios, including recycled water. The models also enable the user to apply multiple climate change scenarios, including normal, moderate drought, severe drought, and wet weather conditions.

ForagerNet3_Demography_V3

Andrew White | Published Tuesday, November 29, 2016

The ForagerNet3_Demography model is a non-spatial ABM designed to serve as a platform for exploring several aspects of hunter-gatherer demography.

We present an Agent-Based Stock Flow Consistent Multi-Country model of a Currency Union to analyze the impact of changes in the fiscal regimes that is permanent changes in the deficit-to-GDP targets that governments commit to comply.

Livestock drought insurance model

Birgit Müller Felix John Jürgen Groeneveld Karin Frank Russell Toth | Published Tuesday, December 19, 2017 | Last modified Saturday, April 14, 2018

The model analyzes the economic and ecological effects of a provision of livestock drought insurance for dryland pastoralists. More precisely, it yields qualitative insights into how long-term herd and pasture dynamics change through insurance.

Urban Teacher Lifecycle and Mobility

Yevgeny Patarakin | Published Wednesday, July 23, 2025

This agent-based model simulates the lifecycle, movement, and satisfaction of teachers within an urban educational system composed of multiple universities and schools. Each teacher agent transitions through several possible roles: newcomer, university student, unemployed graduate, and employed teacher. Teachers’ pathways are shaped by spatial configuration, institutional capacities, individual characteristics, and dynamic interactions with schools and universities. Universities are assigned spatial locations with a controllable level of centralization and are characterized by academic ratings, capacity, and alumni records. Schools are distributed throughout the city, each with a limited number of vacancies, hiring requirements, and offered salaries. Teachers apply to universities based on the alignment of their personal academic profiles with institutional ratings, pursue studies, and upon graduation become candidates for employment at schools.
The employment process is driven by a decentralized matching of teacher expectations and school offers, taking into account factors such as salary, proximity, and peer similarity. Teachers’ satisfaction evolves over time, reflecting both institutional characteristics and the composition of their colleagues; low satisfaction may prompt teachers to transfer between schools within their mobility radius. Mortality and teacher attrition further shape workforce dynamics, leading to continuous recruitment of newcomers to maintain a stable population. The model tracks university reputation through the academic performance and number of alumni, and visualizes key metrics including teacher status distribution, school staffing, university alumni counts, and overall satisfaction. This structure enables the exploration of policy interventions, hiring and training strategies, and the impact of spatial and institutional design on the allocation, retention, and happiness of urban educational staff.

The role of spatial foresight in models of hominin dispersal

Colin Wren | Published Monday, February 24, 2014 | Last modified Monday, July 14, 2014

The natural selection of foresight, an accuracy at assess the environment, under degrees of environmental heterogeneity. The model is designed to connect local scale mobility, from foraging, with the global scale phenomenon of population dispersal.

Market for Protection

Steven Doubleday | Published Monday, July 01, 2013 | Last modified Monday, August 19, 2013

Simulation to replicate and extend an analytical model (Konrad & Skaperdas, 2010) of the provision of security as a collective good. We simulate bandits preying upon peasants in an anarchy condition.

Displaying 10 of 963 results for "J Van Der Beek" 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