Boids: In 1986 I made a computer model of coordinated animal motion such as bird flocks and fish schools. It was based on three dimensional computational geometry of the sort normally used in computer animation or computer aided design. I called the generic simulated flocking creatures boids. The basic flocking model consists of three simple steering behaviors which describe how an individual boid maneuvers based on the positions and velocities its nearby flockmates: ..

References in zbMATH (referenced in 327 articles )

Showing results 1 to 20 of 327.
Sorted by year (citations)

1 2 3 ... 15 16 17 next

  1. Almeida, Ricardo; Kamocki, Rafał; Malinowska, Agnieszka B.; Odzijewicz, Tatiana: Optimal leader-following consensus of fractional opinion formation models (2021)
  2. Ávila-Martínez, Eber Jafet; Barajas-Ramírez, Juan Gonzalo: Flocking motion in swarms with limited sensing radius and heterogeneous input constraints (2021)
  3. Clusella, Pau; Pastor-Satorras, Romualdo: Phase transitions on a class of generalized vicsek-like models of collective motion (2021)
  4. Dong, Jiu-Gang; Ha, Seung-Yeal; Kim, Doheon: Emergence of mono-cluster flocking in the thermomechanical Cucker-Smale model under switching topologies (2021)
  5. Efremov, A. Yu.; Legovich, Yu. S.: Flocking control of small unmanned aerial vehicles in obstacle field (2021)
  6. Freitas, Vander L. S.; Yanchuk, Serhiy; Zaks, Michael; Macau, Elbert E. N.: Synchronization-based symmetric circular formations of mobile agents and the generation of chaotic trajectories (2021)
  7. Gao, Jian; Gu, Changgui; Yang, Huijie; Wang, Man: A flight formation mechanism: the weight of repulsive force (2021)
  8. Ha, Seung-Yeal; Jung, Jinwook; Röckner, Michael: Collective stochastic dynamics of the Cucker-Smale ensemble under uncertain communication (2021)
  9. Lee, Hyun Keun; Yeo, Kangmo; Hong, Hyunsuk: Collective steady-state patterns of swarmalators with finite-cutoff interaction distance (2021)
  10. Liu, Shuai; Zhang, Li: Distributed consensus and convergence rate analysis of multiagent systems with noises under (G)-expectation (2021)
  11. Lymburn, Thomas; Algar, Shannon D.; Small, Michael; Jüngling, Thomas: Reservoir computing with swarms (2021)
  12. Thrun, Michael C.; Ultsch, Alfred: Swarm intelligence for self-organized clustering (2021)
  13. Tong, Xin T.; Choi, Kwok Pui; Lai, Tze Leung; Wong, Weng Kee: Stability bounds and almost sure convergence of improved particle swarm optimization methods (2021)
  14. Zhao, Can; Liu, Xinzhi; Zhong, Shouming; Shi, Kaibo; Liao, Daixi; Zhong, Qishui: Leader-following consensus of multi-agent systems via novel sampled-data event-triggered control (2021)
  15. Zöller, Marc-André; Huber, Marco F.: Benchmark and survey of automated machine learning frameworks (2021)
  16. Beaver, Logan; Malikopoulos, Andreas A.: An energy-optimal framework for assignment and trajectory generation in teams of autonomous agents (2020)
  17. Billiard, Sylvain; Derex, Maxime; Maisonneuve, Ludovic; Rey, Thomas: Convergence of knowledge in a stochastic cultural evolution model with population structure, social learning and credibility biases (2020)
  18. Burger, Martin; Pinnau, René; Totzeck, Claudia; Tse, Oliver; Roth, Andreas: Instantaneous control of interacting particle systems in the mean-field limit (2020)
  19. Cao, Fei; Motsch, Sebastien; Reamy, Alexander; Theisen, Ryan: Asymptotic flocking for the three-zone model (2020)
  20. Cheng, Jianfei; Chen, Maoli; Wang, Xiao: Flocking behavior of Cucker-Smale model with processing delay (2020)

1 2 3 ... 15 16 17 next