The model explores how two types of information - social (in the form of pheromone trails) and private (in the form of route memories) affect ant colony level foraging in a variable enviroment.

This adaptation of the Relative Agreement model of opinion dynamics (Deffuant et al. 2002) extends the Meadows and Cliff (2012) implementation of this model in a manner that explores the effect of the network structure among the agents.

The CHIME ABM explores information distribution networks and agents’ protective decision making in the context of hurricane landfall.

The fight against poverty is an urgent global challenge. Microinsurance is promoted as a valuable instrument for buffering income losses due to health or climate-related risks of low-income households in developing countries. However, apart from direct positive effects they can have unintended side effects when insured households lower their contribution to traditional arrangements where risk is shared through private monetary support.

RiskNetABM is an agent-based model that captures dynamics between income losses, insurance payments and informal risk-sharing. The model explicitly includes decisions about informal transfers. It can be used to assess the impact of insurance products and informal risk-sharing arrangements on the resilience of smallholders. Specifically, it allows to analyze whether and how economic needs (i.e. level of living costs) and characteristics of extreme events (i.e. frequency, intensity and type of shock) influence the ability of insurance and informal risk-sharing to buffer income shocks. Two types of behavior with regard to private monetary transfers are explicitly distinguished: (1) all households provide transfers whenever they can afford it and (2) insured households do not show solidarity with their uninsured peers.

The model is stylized and is not used to analyze a particular case study, but represents conditions from several regions with different risk contexts where informal risk-sharing networks between smallholder farmers are prevalent.

…

This work is a java implementation of a study of the viability of a population submitted to floods. The population derives some benefit from living in a certain environment. However, in this environment, floods can occur and cause damage. An individual protection measure can be adopted by those who wish and have the means to do so. The protection measure reduces the damage in case of a flood. However, the effectiveness of this measure deteriorates over time. Individual motivation to adopt this measure is boosted by the occurrence of a flood. Moreover, the public authorities can encourage the population to adopt this measure by carrying out information campaigns, but this comes at a cost. People’s decisions are modelled based on the Protection Motivation Theory (Rogers1975, Rogers 1997, Maddux1983) arguing that the motivation to protect themselves depends on their perception of risk, their capacity to cope with risk and their socio-demographic characteristics.
While the control designing proper informations campaigns to remain viable every time is computed in the work presented in https://www.comses.net/codebases/e5c17b1f-0121-4461-9ae2-919b6fe27cc4/releases/1.0.0/, the aim of the present work is to produce maps of probable viability in case the serie of upcoming floods is unknown as well as much of the parameters for the population dynamics. These maps are bi-dimensional, based on the value of known parameters: the current average wealth of the population and their actual or possible future annual revenues.

（An empty output folder named “NETLOGOexperiment” in the same location with the LAKEOBS_MIX.nlogo file is required before the model can be run properly）
The model is motivated by regime shifts (i.e. abrupt and persistent transition) revealed in the previous paleoecological study of Taibai Lake. The aim of this model is to improve a general understanding of the mechanism of emergent nonlinear shifts in complex systems. Prelimnary calibration and validation is done against survey data in MLYB lakes. Dynamic population changes of function groups can be simulated and observed on the Netlogo interface.
Main functional groups in lake ecosystems were modelled as super-individuals in a space where they interact with each other. They are phytoplankton, zooplankton, submerged macrophyte, planktivorous fish, herbivorous fish and piscivorous fish. The relationships between these functional groups include predation (e.g. zooplankton-phytoplankton), competition (phytoplankton-macrophyte) and protection (macrophyte-zooplankton). Each individual has properties in size, mass, energy, and age as physiological variables and reproduce or die according to predefined criteria. A system dynamic model was integrated to simulate external drivers.
Set biological and environmental parameters using the green sliders first. If the data of simulation are to be logged, set “Logdata” as true and input the name of the file you want the spreadsheet(.csv) to be called. You will need create an empty folder called “NETLOGOexperiment” in the same level and location with the LAKEOBS_MIX.nlogo file. Press “setup” to initialise the system and “go” to start life cycles.

The model, presented here, is a re-implementation of the Pepper and Smuts’ model : - Pepper, J.W. and B.B. Smuts. 2000. “The evolution of cooperation in an ecological context: an agent-based model”. Pp. 45-76 in T.A. Kohler and G.J. Gumerman, eds. Dynamics of human and primate societies: agent-based modeling of social and spatial processes. Oxford University Press, Oxford. - Pepper, J.W. and B.B. Smuts. 2002. “Assortment through Environmental Feedback”. American Naturalist, 160: 205-213 […]

Overview

The Weather model is a procedural generation model designed to create realistic daily weather data for socioecological simulations. It generates synthetic weather time series for solar radiation, temperature, and precipitation using algorithms based on sinusoidal and double logistic functions. The model incorporates stochastic variation to mimic unpredictable weather patterns and aims to provide realistic yet flexible weather inputs for exploring diverse climate scenarios.

The Weather model can be used independently or integrated into larger models, providing realistic weather patterns without extensive coding or data collection. It can be customized to meet specific requirements, enabling users to gain a better understanding of the underlying mechanisms and have greater confidence in their applications.

…

The purpose of this hybrid ABM is to answer the question: where is the best place for a new swimming pool in a region of Krakow (in Poland)?

The model is well described in ODD protocol, that can be found in the end of my article published in JASSS journal (available online: http://jasss.soc.surrey.ac.uk/22/1/1.html ). Comparison of this kind of models with spatial interaction ones, is presented in the article. Before developing the model for different purposes, area of interest or services, I recommend reading ODD protocol and the article.

I published two films on YouTube that present the model: https://www.youtube.com/watch?v=iFWG2Xv20Ss , https://www.youtube.com/watch?v=tDTtcscyTdI&t=1s

…

The model that simulates the dynamic creation and maintenance of knowledge-based formations such as communities of scientists, fashion movements, and subcultures. The model’s environment is a spatial one, representing not geographical space, but a “knowledge space” in which each point is a different collection of knowledge elements. Agents moving through this space represent people’s differing and changing knowledge and beliefs. The agents have only very simple behaviors: If they are “lonely,” that is, far from a local concentration of agents, they move toward the crowd; if they are crowded, they move away.

Running the model shows that the initial uniform random distribution of agents separates into “clumps,” in which some agents are central and others are distributed around them. The central agents are crowded, and so move. In doing so, they shift the centroid of the clump slightly and may make other agents either crowded or lonely, and they too will move. Thus, the clump of agents, although remaining together for long durations (as measured in time steps), drifts across the view. Lonely agents move toward the clump, sometimes joining it and sometimes continuing to trail behind it. The clumps never merge.

The model is written in NetLogo (v6). It is used as a demonstration of agent-based modelling in Gilbert, N. (2008) Agent-Based Models (Quantitative Applications in the Social Sciences). Sage Publications, Inc. and described in detail in Gilbert, N. (2007) “A generic model of collectivities,” Cybernetics and Systems. European Meeting on Cybernetic Science and Systems Research, 38(7), pp. 695–706.