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Submitted by:-
Nitesh Bichwani
(02224302013)
CONTENTS
 Introduction
 What is a Swarm Intelligence (SI)?
 Examples from nature
 Real world examples
 Honey Bee
 Wasps
 Ant
 Inspiration from Nature
 Natural navigation
 Natural clustering
 Bird Flocking
 Ant Colony Optimization
What is Swarm Intelligence (SI)?
•Swarm intelligence (SI) is an artificial intelligence technique based around
the study of collective behavior in decentralized, self-organized systems.
•Introduced by Gerardo Beni and Jing Wang in 1989.
•Typically made up of a population of simple agents.
INTRODUCTION
Examples in natural systems of SI include :
Ant colonies, bee beehive , fish schooling , bird flocking , bacterial
growth, and microbial intelligence.
Fish Schooling
Bird Flocking
Bee Beehive
Ant Colonies
Real world examples
1. Honey Bee
•Colony cooperation
•Regulate hive temperature
•Efficiency via Specialization: division of
labor in the colony
•Communication : Food sources are
exploited according to quality and
distance from the hive.
•Pulp foragers, water foragers & builders
•Complex nests
Horizontal columns
Protective covering
Central entrance hole
2. Wasps
•Organizing highways to and from their
foraging sites by leaving pheromone trails
•Form chains from their own bodies to
create a bridge to pull and hold leafs
together with silk
•Division of labor between major and
minor ants
3. Ants
Inspiration from Nature
1. Natural Navigation
Food
 Ants (blind) navigate from nest to food source
 Shortest path is discovered via pheromone trails
 each ant moves at random, probabilistically
 pheromone is deposited on path
 ants detect lead ant’s path, inclined to follow, i.e.,
more pheromone on path increases probability of path being
followed
Note :-
pheromone trails - Chemicals' secreted from the body of an
individual.
2. Natural Clustering
There are typically three distinct elements of structure:
 The protective and ribbed cone-shaped outer walls (also featuring
ventilation ducts).
 The hive consists of thin horizontal lamellae supported by pillars. A
flat floor structure, sometimes exhibiting cooling vents in a spiral
formation.
 The royal chamber: a thick walled enclosure for the queen, with small
holes in the walls to allow workers in and out. This is usually well
protected underneath the hive structure, and is where the queen lays
her eggs.
3. Bird Flocking
 These flocks may be very large, in the tens of thousands of
birds, and show coordinated turning and wheeling movements.
 The recipe that achieves realistic swarm behaviour is this triplet
of steering behaviours to be followed by each individual in a
swarm:
 Separation: steer to avoid coming too close to others.
 Alignment: steer towards the mean heading of others.
 Cohesion: steer towards the mean position of others.
COLLISION AVOIDANCE
 Rule 1: Avoid Collision with neighboring birds
VELOCITY MATCHING
 Rule 2: Match the velocity of neighboring birds
FLOCK CENTERING
 Rule 3: Stay near neighboring birds
 Inspired by foraging behavior of ants.
 Ants find shortest path to food source from nest.
 Ants deposit pheromone along traveled path which is used by other ants to
follow the trail.
 It has adaptability, robustness and redundancy.
4. Ant Colony Optimization
FORAGING BEHAVIOR OF ANTS
 2 ants start with equal probability of going on either path.
FORAGING BEHAVIOR OF ANTS
 The ant on shorter path has a shorter to-and-fro time
from it’s nest to the food.
FORAGING BEHAVIOR OF ANTS
 The density of pheromone on the shorter path is higher
because of 2 passes by the ant (as compared to 1 by the
other).
FORAGING BEHAVIOR OF ANTS
 The next ant takes the shorter route.
FORAGING BEHAVIOR OF ANTS
 Over many iterations, more ants begin using the path
with higher pheromone, thereby further reinforcing it.
FORAGING BEHAVIOR OF ANTS
 After some time, the shorter path is almost exclusively
used.

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Swarm intelligence

  • 2. CONTENTS  Introduction  What is a Swarm Intelligence (SI)?  Examples from nature  Real world examples  Honey Bee  Wasps  Ant  Inspiration from Nature  Natural navigation  Natural clustering  Bird Flocking  Ant Colony Optimization
  • 3. What is Swarm Intelligence (SI)? •Swarm intelligence (SI) is an artificial intelligence technique based around the study of collective behavior in decentralized, self-organized systems. •Introduced by Gerardo Beni and Jing Wang in 1989. •Typically made up of a population of simple agents. INTRODUCTION
  • 4. Examples in natural systems of SI include : Ant colonies, bee beehive , fish schooling , bird flocking , bacterial growth, and microbial intelligence. Fish Schooling Bird Flocking Bee Beehive Ant Colonies
  • 5. Real world examples 1. Honey Bee •Colony cooperation •Regulate hive temperature •Efficiency via Specialization: division of labor in the colony •Communication : Food sources are exploited according to quality and distance from the hive.
  • 6. •Pulp foragers, water foragers & builders •Complex nests Horizontal columns Protective covering Central entrance hole 2. Wasps
  • 7. •Organizing highways to and from their foraging sites by leaving pheromone trails •Form chains from their own bodies to create a bridge to pull and hold leafs together with silk •Division of labor between major and minor ants 3. Ants
  • 8. Inspiration from Nature 1. Natural Navigation Food
  • 9.  Ants (blind) navigate from nest to food source  Shortest path is discovered via pheromone trails  each ant moves at random, probabilistically  pheromone is deposited on path  ants detect lead ant’s path, inclined to follow, i.e., more pheromone on path increases probability of path being followed Note :- pheromone trails - Chemicals' secreted from the body of an individual.
  • 11. There are typically three distinct elements of structure:  The protective and ribbed cone-shaped outer walls (also featuring ventilation ducts).  The hive consists of thin horizontal lamellae supported by pillars. A flat floor structure, sometimes exhibiting cooling vents in a spiral formation.  The royal chamber: a thick walled enclosure for the queen, with small holes in the walls to allow workers in and out. This is usually well protected underneath the hive structure, and is where the queen lays her eggs.
  • 12. 3. Bird Flocking  These flocks may be very large, in the tens of thousands of birds, and show coordinated turning and wheeling movements.  The recipe that achieves realistic swarm behaviour is this triplet of steering behaviours to be followed by each individual in a swarm:  Separation: steer to avoid coming too close to others.  Alignment: steer towards the mean heading of others.  Cohesion: steer towards the mean position of others.
  • 13. COLLISION AVOIDANCE  Rule 1: Avoid Collision with neighboring birds
  • 14. VELOCITY MATCHING  Rule 2: Match the velocity of neighboring birds
  • 15. FLOCK CENTERING  Rule 3: Stay near neighboring birds
  • 16.  Inspired by foraging behavior of ants.  Ants find shortest path to food source from nest.  Ants deposit pheromone along traveled path which is used by other ants to follow the trail.  It has adaptability, robustness and redundancy. 4. Ant Colony Optimization
  • 17. FORAGING BEHAVIOR OF ANTS  2 ants start with equal probability of going on either path.
  • 18. FORAGING BEHAVIOR OF ANTS  The ant on shorter path has a shorter to-and-fro time from it’s nest to the food.
  • 19. FORAGING BEHAVIOR OF ANTS  The density of pheromone on the shorter path is higher because of 2 passes by the ant (as compared to 1 by the other).
  • 20. FORAGING BEHAVIOR OF ANTS  The next ant takes the shorter route.
  • 21. FORAGING BEHAVIOR OF ANTS  Over many iterations, more ants begin using the path with higher pheromone, thereby further reinforcing it.
  • 22. FORAGING BEHAVIOR OF ANTS  After some time, the shorter path is almost exclusively used.