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Emergent Behavior in Biological Swarms

Emergent Behavior in Biological Swarms. Stephen Motter. The Papers. The Self-Organizing Exploratory Pattern of the Argentine Ant Study of Group Food Retrieval by Ants as a Model for Multi-Robot Collective Transport. 1. Paper 1.

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Emergent Behavior in Biological Swarms

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  1. Emergent Behavior in Biological Swarms Stephen Motter

  2. The Papers • The Self-Organizing Exploratory Pattern of the Argentine Ant • Study of Group Food Retrieval by Ants as a Model for Multi-Robot Collective Transport 1

  3. Paper 1 The Self-Organizing Exploratory Pattern of the Argentine Ant • Authors: • J. L. Deneubourg • S. Aron • S. Goss • J. M. Pasteels • Appeared in the Journal of Insect Behavior, 1990 2

  4. Critique Paper 1 Problem Insights Approach Experiment Results Problem Statement • How do ants explore? • Rather, how is a single ant’s exploration affected by the previous ants? Is it a function? Can we model it? • Homogenous/heterogeneous agents? 3

  5. Critique Paper 1 Problem Insights Approach Experiment Results Insights • Ants explore with no fixed destination. • They do this at night (so no visual cues). • The Argentine ant lays her pheromone continuously (not just on return). 4

  6. Critique Paper 1 Problem Insights Approach Experiment Results Approach • Observe the exploratory pattern. • Reduce to a binary choice (diamond bridge). • Generate a model from observed data. • Does a Monte-Carlo model fit? • General choice function: 5

  7. Critique Paper 1 Problem Insights Approach Experiment Results Experiment (Open Arena) • This experiment has two parts. • Empty arena (no food or debris). • Automatically photographed every 60 seconds. • Sand periodically replaced. Note: This is an artist’s rendition of the experiment, as no image of the arena was provided by the authors. 6

  8. Critique Paper 1 Problem Insights Approach Experiment Results Experiment (Diamond Bridge) • The second part is more controlled. • Ants crossing bridge counted every 3-minutes. • Ants prevented from doubling back. 7

  9. Critique Paper 1 Problem Insights Approach Experiment Results Results (Open Arena) • Ants explore close to the nest first. • The front advances, but leaves a trail. • Number of explorers grows logistically. • Picking out returning explorers halts exploration development. • Ants will not ‘re-explore’ a well-explored area. 8

  10. Critique Paper 1 Problem Insights Approach Experiment Results Results (Open Arena) 9

  11. Critique Paper 1 Problem Insights Approach Experiment Results Results (Diamond Bridge) • Both branches chosen equally at first. • Positive feedback rapidly makes one path preferable. • Ants act reactively (as a function of # ant passages). 10

  12. Critique Paper 1 Problem Insights Approach Experiment Results Results (Diamond Bridge) (Note: The axes on these graphs are not the same) 11

  13. Critique Paper 1 Problem Insights Approach Experiment Results Critique • The model fits, but a lot of simplifications are required. • Pheromone quantity estimated by number of ants passing (ignores evaporation, assumes each ant lays equal amount of pheromone). • The ‘separated ants’ appear more dispersed in experiments than model. 12

  14. Paper 2 Study of Group Food Retrieval by Ants as a Model for Multi-Robot Collective Transport • Authors: • S. Berman • Q. Lindsey • V. Kumar • M. S. Sakar • S. C. Pratt • Appeared in the Proceedings of the IEEE, 2011 13

  15. Critique Paper 2 Problem Insights Approach Experiment Results Problem Statement • What is the role of each ant in collective transport? Rules that govern their actions? • Can we apply this to robots who, like ants. have limited sensing, communication, and computation capabilities? 14

  16. Critique Paper 2 Problem Insights Approach Experiment Results Insights • Ants grab stuff in groups (better than robots do). • The ant approach is decentralized, scalable, a requires no a priori information. • Therefore, ants are more flexible and more robust than centralized approach. • Prey transport teams are superefficient. 15

  17. Critique Paper 2 Problem Insights Approach Experiment Results Approach • Observe ants in a controlled environment. • Develop a behavior model. • Run a simulation to see if the model matches. 16

  18. Critique Paper 2 Problem Insights Approach Experiment Results Experiment • Fabricate fake food (out of springs and fig paste) and measure the forces and deformations as ants carry it back to the nest (about 1 meter). • 27 Trials 17

  19. Critique Paper 2 Problem Insights Approach Experiment Results Results (Observation) • Quasi-static motion • More ants is better (faster) • Load speed saturation with increased group size 18

  20. Critique Paper 2 Problem Insights Approach Experiment Results Results (Simulation) • Hybrid system with probabilistic transitions between two task modes: • search for grasp point • transport • Start from uniformly randomly distributed positions and orientations 19

  21. Critique Paper 2 Problem Insights Approach Experiment Results Critique • Friction is a major factor which throws the deformation measures off. • They even observe “stick-slip” motion. 20

  22. Closing Thoughts • Both use ants as a model of homogenous agents and minimal communication. • Both attempt to apply lessons from ants to distributed robotics. • Both simulations use very simple models, while still being reasonably accurate. 21

  23. Questions? • The Self-Organizing Exploratory Pattern of the Argentine Ant • Study of Group Food Retrieval by Ants as a Model for Multi-Robot Collective Transport 22

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