NetLogo

NetLogo, a Multi-agent Simulation Environment. NetLogo [Wilensky, 1999] is a multi-agent programming language and modeling environment for simulating complex phenomena. It is designed for both research and education and is used across a wide range of disciplines and education levels. In this paper we focus on NetLogo as a tool for research and for teaching at the undergraduate level and higher. We outline the principles behind our design and describe recent and planned enhancements


References in zbMATH (referenced in 47 articles )

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  1. Kimbrough, Steven Orla; Lau, Hoong Chuin: Business analytics for decision making (2016)
  2. Lenhart, Suzanne; Xiong, Jie; Yong, Jiongmin: Optimal controls for stochastic partial differential equations with an application in population modeling (2016)
  3. An, Gary; Kulkarni, Swati: An agent-based modeling framework linking inflammation and cancer using evolutionary principles: description of a generative hierarchy for the hallmarks of cancer and developing a bridge between mechanism and epidemiological data (2015)
  4. Foo, Jasmine; Haskell, Cymra; Komarova, Natalia L.; Segal, Rebecca A.; Wood, Karen E.: Modeling sympatric speciation in quasiperiodic environments (2015)
  5. Hoyles, Celia; Noss, Richard: A computational lens on design research (2015)
  6. Monk, Travis; Paulin, Michael G.; Green, Peter: Ecological constraints on the origin of neurones (2015)
  7. Oremland, Matthew; Laubenbacher, Reinhard: Optimal harvesting for a predator-prey agent-based model using difference equations (2015)
  8. Salgado, Mauricio: The evolution of paternal care can lead to population growth in artificial societies (2015)
  9. Berland, Matthew; Baker, Ryan S.; Blikstein, Paulo: Educational data mining and learning analytics: applications to constructionist research (2014)
  10. Dong, Mianxiong; Ota, Kaoru; Li, He; Du, Suguo; Zhu, Haojin; Guo, Song: RENDEZVOUS: towards fast event detecting in wireless sensor and actor networks (2014)
  11. Lai, Kevin; White, Tobin: How groups cooperate in a networked geometry learning environment (2014)
  12. Lipinski-Paes, Thiago; de Souza, Osmar Norberto: MASTERS: a general sequence-based multiagent system for protein tertiary structure prediction (2014)
  13. Moein, Sara; Logeswaran, Rajasvaran: KGMO: a swarm optimization algorithm based on the kinetic energy of gas molecules (2014)
  14. Patil, Akshay P.; Dongre, Alpana R.: Emergent properties of the public realm and encroachments in the urban environment (2014)
  15. Wang, Pei; Tian, Chengeng; Lu, Jun-An: Identifying influential spreaders in artificial complex networks (2014)
  16. Wilkerson-Jerde, Michelle Hoda: Construction, categorization, and consensus: student generated computational artifacts as a context for disciplinary reflection (2014)
  17. Brady, Corey; White, Tobin; Davis, Sarah; Hegedus, Stephen: SimCalc and the networked classroom (2013)
  18. Janošek, Michal; Kocian, Václav; Volná, Eva: Complex system simulation parameters settings methodology (2013)
  19. Pape, Andreas Duus; Kurtz, Kenneth J.: Evaluating case-based decision theory: predicting empirical patterns of human classification learning (2013)
  20. Stradner, Jürgen; Thenius, Ronald; Zahadat, Payam; Hamann, Heiko; Crailsheim, Karl; Schmickl, Thomas: Algorithmic requirements for swarm intelligence in differently coupled collective systems (2013)

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Further publications can be found at: https://ccl.northwestern.edu/netlogo/references.shtml