Simulates impacts of ants killing colony mates when in conflict with another nest. The murder rate is adjustable, and the environmental change is variable. The colonies employ social learning so knowledge diffusion proceeds if interactions occur.
Biobehavioral interactions between two populations under different movement strategies.
The model simulates interactions in small, task focused groups that might lead to the emergence of status beliefs among group members.
The model reproduces the spread of environmental awareness among agents and the impact of awareness level of the agents on the consumption of a resource, like energy. An agent is a household with a set of available advanced smart metering functions.
Agent-based model of hunting behavior of Ache hunter-gatherers from Paraguay. We evaluate the effect of group size and cooperative hunting
Replication of the well known Artificial Anasazi model that simulates the population dynamics between 800 and 1350 in the Long House Valley in Arizona.
CoMSES Net is dedicated to fostering open and reproducible scientific computation through cyberinfrastructure and community development. We develop and curate resources for model-based science with FAQs and forums for discussions, job postings, and events. We also develop and maintain the OpenABM Computational Model Library, a digital repository for code that supports discovery and good practices for software citation, reproducibility and reuse.
Postdoc position The Department of Civil and Environmental Engineering in the P.C. Rossin College of Engineering and Applied Science at Lehigh University is seeking a multi-disciplinary post-doct[...]
Full-time postdoc research position for integrated crop modeling in the context of climate change and food security temporarily limited to 3 years at our location in Müncheberg beginning 1 March 2019. Application deadline is January 28, 2019. Please send your application preferably by e-mail (one PDF file, max. 5 MB) with the usual documents (cover letter, curriculum vitae, and names of three references) stating the reference number 05-2019 until 28th January 2019 to: Bewerbungen@zalf.de.
The goal of this program is to enable RStudio employees to collaborate with students to do work that will help both RStudio users and the broader R community, and help ensure that the community of R developers is as diverse as its community of users. Over the course of the internship, you will work with experienced data scientists, software developers, and educators to create and share new tools and ideas.
