Your SlideShare is downloading. ×
  • Like
Swarm Intelligence
Upcoming SlideShare
Loading in...5

Thanks for flagging this SlideShare!

Oops! An error has occurred.


Now you can save presentations on your phone or tablet

Available for both IPhone and Android

Text the download link to your phone

Standard text messaging rates apply

Swarm Intelligence



Published in Science , Technology
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
    Be the first to like this
No Downloads


Total Views
On SlideShare
From Embeds
Number of Embeds



Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

    No notes for slide


  • 1. Swarm Intelligence Kasun Ranga Wijeweera (
  • 2. A Natural Swarm Intelligence System (Ant Colony) • Find the shortest path to food • Go on raiding parties to gather it • Carry it cooperatively • Make cemeteries • Sort their brood by size • Etc
  • 3. What is Swarm Intelligence? • Collective system capable of accomplishing difficult tasks in dynamic and varied environments without any external guidance or control and with no central coordination • Achieving a collective performance which could not normally be achieved by an individual acting alone
  • 4. Types of Interactions of Ants • Direct interactions – Food/liquid exchange – Visual contact – Chemical contact (pheromones) • Indirect interactions (Stigmergy) – Individual behavior modifies the environment, which in turn modifies the behavior of other individuals
  • 5. Designing Algorithms • Algorithms can be designed by observing the behavior of ants • It means the coordination of artificial ants for solving computational problems Dr. Marco Dorigo
  • 6. Travelling Salesman Problem Initialize Loop /* at this level each loop is called an iteration */ Each ant is positioned on a starting node Loop /* at this level each loop is called a step */ Each ant applies a state transition rule to incrementally build a solution and a local pheromone updating rule Until all ants have built a complete solution A global pheromone updating rule is applied Until End condition M. Dorigo, L. M. Gambardella : Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem
  • 7. Travelling Sales Ants
  • 8. Application in Robotics • Complete tasks collectively • No need to have extremely complex algorithms • Adaptable to changing environment
  • 9. Communication Networks • Routing packets to destination in shortest time • Similar to shortest route • Statistics kept from prior routing
  • 10. Challenges • Still very theoretical • No clear boundaries • Details about inner workings of swarms
  • 11. Any Questions?
  • 12. Thank You!