AMIRIS is the Agent-based Market model for the Investigation of Renewable and Integrated energy Systems.

It is an agent-based simulation of electricity markets and their actors.
AMIRIS enables researches to analyse and evaluate energy policy instruments and their impact on the actors involved in the simulation context.
Different prototypical agents on the electricity market interact with each other, each employing complex decision strategies.
AMIRIS allows to calculate the impact of policy instruments on economic performance of power plant operators and marketers.
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Individually parameterized mussels (Mytilus californianus) recruit, grow, move and die in a 3D environment while facing predation (in the form of seastar agents), heat and desiccation with increased tide height, and storms. Parameterized with data collected by Wootton, Paine, Kandur, Donahue, Robles and others. See my 2019 CoMSES video presentation to learn more.

A multithreaded replication of the PPHPC model in Java for testing different ABM parallelization strategies.

This is a replication of the SequiaBasalto model, originally built in Cormas by Dieguez Cameroni et al. (2012, 2014, Bommel et al. 2014 and Morales et al. 2015). The model aimed to test various adaptations of livestock producers to the drought phenomenon provoked by climate change. For that purpose, it simulates the behavior of one livestock farm in the Basaltic Region of Uruguay. The model incorporates the price of livestock, fodder and paddocks, as well as the growth of grass as a function of climate and seasons (environmental submodel), the life cycle of animals feeding on the pasture (livestock submodel), and the different strategies used by farmers to manage their livestock (management submodel). The purpose of the model is to analyze to what degree the common management practices used by farmers (i.e., proactive and reactive) to cope with seasonal and interannual climate variations allow to maintain a sustainable livestock production without depleting the natural resources (i.e., pasture). Here, we replicate the environmental and livestock submodel using NetLogo.

One year is 368 days. Seasons change every 92 days. Each day begins with the growth of grass as a function of climate and season. This is followed by updating the live weight of cows according to the grass height of their patch, and grass consumption, which is determined based on the updated live weight. After consumption, cows grow and reproduce, and a new grass height is calculated. Cows then move to the patch with less cows and with the highest grass height. This updated grass height value will be the initial grass height for the next day.

The purpose of this model is to analyze how different management strategies affect the wellbeing, sustainability and resilience of an extensive livestock system under scenarios of climate change and landscape configurations. For this purpose, it simulates one cattle farming system, in which agents (cattle) move through the space using resources (grass). Three farmer profiles are considered: 1) a subsistence farmer that emphasizes self-sufficiency and low costs with limited attention to herd management practices, 2) a commercial farmer focused on profit maximization through efficient production methods, and 3) an environmental farmer that prioritizes conservation of natural resources and animal welfare over profit maximization. These three farmer profiles share the same management strategies to adapt to climate and resource conditions, but differ in their goals and decision-making criteria for when, how, and whether to implement those strategies. This model is based on the SequiaBasalto model (Dieguez Cameroni et al. 2012, 2014, Bommel et al. 2014 and Morales et al. 2015), replicated in NetLogo by Soler-Navarro et al. (2023).

One year is 368 days. Seasons change every 92 days. Each step begins with the growth of grass as a function of climate and season. This is followed by updating the live weight of animals according to the grass height of their patch, and grass consumption, which is determined based on the updated live weight. Animals can be supplemented by the farmer in case of severe drought. After consumption, cows grow and reproduce, and a new grass height is calculated. This updated grass height value becomes the starting grass height for the next day. Cows then move to the next area with the highest grass height. After that, cattle prices are updated and cattle sales are held on the first day of fall. In the event of a severe drought, special sales are held. Finally, at the end of the day, the farm balance and the farmer’s effort are calculated.