1. Swarm intelligence Self-organization in nature and how we can learn from it

2. Content What is swarm intelligence? The benefits of being in a swarm. How does swarm intelligence solve complex problems? What can we learn from swarms?

3. 1. WHAT IS SWARM INTELLIGENCE? “What is it that governs here? What is it that issues orders, foresees the future, elaborates plans, and preserves equilibrium?” -- Maurice Maeterlinck

4. What is swarm intelligence? The emergent collective intelligence of groups of relatively simple individuals Introduced by Gerardo Beni and Jing Wang in 1989, in the context of cellular robotic systems.

5. What is swarm intelligence? Some characteristics of swarms: – No one is in charge, autonomy – Local information – Simple rules – Complex patterns and behavior of a group Swarm intelligence doesn’t mean all swarms are intelligent (consider a crowd of humans)

6. What is swarm intelligence? Some examples in the nature: – A school of fish A school of fish – A herd of wildebeests A herd of wildebeests – A swarm of locusts A swarm of locusts – A flock of birds A flock of birds

7. 2. THE BENEFITS “and the thousands of fishes moved as a huge beast, piercing the water. They appeared united, inexorably bound to a common fate…” -- Anonymous, 17 th Century

8. The benefits Better defense against predators – Trafalgar Effect – Creating confusion – Unity Is Strength – “Selfish herd”

9. The benefits Increase foraging efficiency Hydro/aerodynamic advantage

10. 3. SWARMS SOLVING COMPLICATED PROBLEMS "... Our latest evil plan and create an army of giant ants to take over the galaxy..." --Dark Helmet from Spaceballs

11. Solving complicated problems Examples – The foraging strategy in ants – Bees “vote” out the best hive site during migration – Termites build colossal mounds that are very well ventilated and thermo- regulated

12. Solving complicated problems An Case study: Foraging strategy in ants 1.Ants wander randomly in the beginning. 2.Upon finding food, they will return to their nest while laying down pheromone trails. 3.Other ants are attracted to follow this trail and reinforce it if they eventually find food too. 4.Pheromone evaporates as time passes. 5.A shorter path will relatively be visited by more ants and hence maintain the pheromone density.

13. 4. WHAT CAN WE LEARN FROM SWARMS? Go to the ant, thou sluggard; consider her ways and be wise: Which having no guide, overseer or ruler, Provideth her meat in the summer, and gathereth her food in the harvest. -- Book of Proverbs

14. Learning from swarms The Travelling Salesman Problem (TSP) “given a number of cities and the costs of travelling from any city to any other city, what is the least-cost round-trip route that visits each city exactly once and then returns to the starting city?”

15. Learning from swarms A simple example of TSP

16. Learning from swarms A harder example of TSP

17. Learning from swarms Initialize the number of ants n, and other parameters. While (the end criterion is not met) do t = t + 1; For k = 1 to n ant k is positioned on a starting node; For m = 2 to problem_size Choose the state to move into according to the probabilistic transition rules; Append the chosen move into tabu k (t) for the ant k ; Next m Compute the length L k (t) of the tour T k (t) chosen by the ant k ; Compute Δτ i,j (t) for every edge (i,j) in T k (t) Next k Update the trail pheromone intensity for every edge (i,j) Compare and update the best solution; End While

18. Learning from swarms More applications – Network routing – Scheduling airlines – Making The Lion King

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