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 116 articles )

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  1. Xiao, Sa; Zhao, Liang; Zhang, Jia-Lin; Wang, Xiang-Tai; Chen, Shu-Yan: Comparing neutral and trade-off community models in shaping the community biomass-diversity relationship under different disturbance levels (2013)
  2. Alexandridis, Kostas; Maru, Yiheyis: Collapse and reorganization patterns of social knowledge representation in evolving semantic networks (2012) ioport
  3. Bodi, Michael; Thenius, Ronald; Szopek, Martina; Schmickl, Thomas; Crailsheim, Karl: Interaction of robot swarms using the honeybee-inspired control algorithm BEECLUST (2012)
  4. Cases, Blanca; Rebollo, Israel; Graña, Manuel: A hybrid spatial-social-logical model explaining human behaviour in emergency situations (2012) ioport
  5. Li, Kang; Gao, Hongwei; Song, Li; Hu, Ping; Wang, Kun; Chen, Chunrui: Local strategic interaction in 2-neighborhood on the endogenous network and its simulations (2012)
  6. Achten, Peter: The Soccer-Fun project (2011)
  7. Stroup, Walter M.; Hills, Thomas; Carmona, Guadalupe: Computing the average square: an agent-based introduction to aspects of current psychometric practice (2011) MathEduc
  8. Sueur, Cédric; Deneubourg, Jean-Louis; Petit, Odile; Couzin, Iain D.: Group size, grooming and fission in primates: a modeling approach based on group structure (2011)
  9. Damaceanu, Romulus-Catalin: Applied computational mathematics in social sciences (2010)
  10. Fridman, Natalie; Kaminka, Gal A.: Modeling pedestrian crowd behavior based on a cognitive model of social comparison theory (2010) ioport
  11. Read, Dwight: Agent-based and multi-agent simulations: Coming of age or in search of an identity? (2010) ioport
  12. Abrahamson, Dor: Embodied design: Constructing means for constructing meaning (2009) MathEduc
  13. An, Gary: A model of TLR4 signaling and tolerance using a qualitative, particle-event-based method: Introduction of spatially configured stochastic reaction chambers (SCSRC) (2009)
  14. Blikstein, Paulo; Wilensky, Uri: An atom is known by the company it keeps: A constructionist learning environment for materials science using agent-based modeling (2009) MathEduc
  15. Chen, Shu-Yan; Xu, Jin; Maestre, Fernando T.; Chu, Cheng-Jin; Wang, Gang; Xiao, Sa: Beyond dual-lattice models: incorporating plant strategies when modeling the interplay between facilitation and competition along environmental severity gradients (2009)
  16. Kefalas, Petros; Stamatopoulou, Ioanna; Sakellariou, Ilias; Eleftherakis, George: Transforming communicating X-machines into P systems (2009)
  17. Michel, Olivier; Spicher, Antoine; Giavitto, Jean-Louis: Rule-based programming for integrative biological modeling. Application to the modeling of the (\lambda) phage genetic switch (2009)
  18. Nebti, Salima; Meshoul, Souham: Predator prey optimization for snake-based contour detection (2009)
  19. Pelta, David; Cruz, Carlos; González, Juán Ramón: A study on diversity and cooperation in a multiagent strategy for dynamic optimization problems (2009)
  20. Rezaei, Golriz; Kirley, Michael: The effects of time-varying rewards on the evolution of cooperation (2009) ioport

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