Flocks, herds and schools: A distributed behavioral model
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Designing emergent behaviors: from local interactions to collective intelligence
Proceedings of the second international conference on From animals to animats 2 : simulation of adaptive behavior: simulation of adaptive behavior
ICICIC '06 Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 3
Self-Organized Pedestrian Crowd Dynamics: Experiments, Simulations, and Design Solutions
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Turning with the Others: Novel Transitions in an SPP Model with Coupling of Accelerations
SASO '08 Proceedings of the 2008 Second IEEE International Conference on Self-Adaptive and Self-Organizing Systems
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
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ISCIS'06 Proceedings of the 21st international conference on Computer and Information Sciences
Stability of a one-dimensional discrete-time asynchronous swarm
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Self-organized flocking with a mobile robot swarm: a novel motion control method
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
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Flocking motions have been the subject of hundreds of studies over the past six decades. The vast majority of models have nearly identical aims: bottom-up demonstration of basic emergent flocking motions. Despite a significant fraction of the literature providing algorithmic descriptions of models, incompleteness and imprecision are also readily identifiable in flocking algorithms, algorithmic input, and validation of the models. To address this issue, this meta-study introduces a data-flow template, which unifies many of the existing approaches. Additionally, there are small differences and ambiguities in the flocking scenarios being studied by different researchers; unfortunately, these differences are of considerable significance. For example, much subtlety is needed to specify sensory requirements exactly and minor modifications may critically alter a flock's exhibited motions. We introduce two taxonomies that minimize both incompleteness and imprecision, and enable us to highlight those publications that study flocking motions under comparable assumptions. Furthermore, we aggregate and translate the publications into a consolidated notation. The common notation along with the data-flow template and the two taxonomies constitute a collection of tools, that together, facilitates complete and precise flocking motion models, and enables much of the work to be unified. To conclude, we make recommendations for more diverse research directions and propose criteria for rigorous problem definitions and descriptions of future flocking motion models.