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

4. Problem 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? Paper 1 Critique ResultsExperimentApproachInsights Problem Statement 3

5. Insights Problem 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). Paper 1 Critique ResultsExperimentApproach Insights 4

6. Approach Problem 1)Observe the exploratory pattern. 2)Reduce to a binary choice (diamond bridge). 3)Generate a model from observed data. – Does a Monte-Carlo model fit? – General choice function: Paper 1 Critique ResultsExperimentInsights Approach 5

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

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

9. Results Problem 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. Paper 1 Critique ExperimentApproachInsights Results (Open Arena) 8

10. Results ProblemPaper 1 Critique ExperimentApproachInsights Results (Open Arena) 9

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

12. Results ProblemPaper 1 Critique ExperimentApproachInsights Results (Diamond Bridge) 11 (Note: The axes on these graphs are not the same)

13. Critique Problem 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. Paper 1ResultsExperimentApproachInsights Critique 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. Problem 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? Paper 2 Critique ResultsExperimentApproachInsights Problem Statement 14

16. Insights Problem 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. Paper 2 Critique ResultsExperimentApproach Insights 15

17. Approach Problem 1)Observe ants in a controlled environment. 2)Develop a behavior model. 3)Run a simulation to see if the model matches. Paper 2 Critique ResultsExperimentInsights Approach 16

18. Experiment Problem 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 Paper 2 Critique ResultsApproachInsights Experiment 17

19. 18 Results ProblemPaper 2 Critique ExperimentApproachInsights Results (Observation) Quasi-static motion More ants is better (faster) Load speed saturation with increased group size

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

21. Critique Problem Friction is a major factor which throws the deformation measures off. They even observe “stick-slip” motion. Paper 2ResultsExperimentApproachInsights Critique 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