swarm intelligence

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Swarm intelligence. Self-organization in nature and how we can learn from it . 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?. - PowerPoint PPT Presentation

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Swarm intelligence

Self-organization in nature and how we can learn from it

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?

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

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.

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)

What is swarm intelligence?

• Some examples in the nature:– A school of fish– A herd of wildebeests– A swarm of locusts– A flock of birds

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, 17th Century

The benefits

• Better defense against predators– Trafalgar Effect– Creating confusion– Unity Is Strength– “Selfish herd”

The benefits

• Increase foraging efficiency• Hydro/aerodynamic advantage

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

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

Solving complicated problems

• An Case study: Foraging strategy in ants1. 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.

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

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?”

Learning from swarms

• A simple example of TSP

Learning from swarms

• A harder example of TSP

Learning from swarmsInitialize the number of ants n, and other parameters.While (the end criterion is not met) do

t = t + 1;For k = 1 to n

antk 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 tabuk(t) for the antk;

Next mCompute the length Lk(t) of the tour Tk(t) chosen by the antk;Compute Δτi,j(t) for every edge (i,j) in Tk(t)

Next kUpdate the trail pheromone intensity for every edge (i,j)Compare and update the best solution;

End While

Learning from swarms

• More applications– Network routing– Scheduling airlines– Making The Lion King

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