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An introduction to Swarm Intelligence, the most popular algorithms used and the applications of swarm intelligence....

An introduction to Swarm Intelligence, the most popular algorithms used and the applications of swarm intelligence.

This presentation talks about the Ant Colony Optimization and the Particle Swarm Optimization, while mentioning the other algorithms used.

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Swarm Intelligence - An Introduction Swarm Intelligence - An Introduction Presentation Transcript

  • Swarm intelligence
    “The emergent collective intelligence of groups of simple agents.”
  • What?
    Collective behavior of decentralized, self-organizing systems
    Natural or Artificial
    Simple local behavior leads to global intelligent behavior
    Ant colonies, bird flocking, bacterial growth
    2
    Swarm Intelligence
  • Why is it of Interest?
    Distributed system of interacting autonomous agents
    Goals: performance optimization and robustness
    Division of labor and distributed task allocation
    Self-organized control and cooperation (decentralized)
    Swarm Intelligence
    3
    View slide
  • Nature
    Swarm Intelligence
    4
    View slide
  • Ant Foraging Behavior
    Shortest path between food and nest
    Indirect Communication – Pheromones
    Ant productivity is better than the sum of their single activities
    Cooperation and Division of Labor
    5
    Swarm Intelligence
  • Ant Colony Optimization (ACO)
    Probabilistic Technique for Solving Computational Problems
    Graph Problems
    Depends on two factors
    Attractiveness of the move from node i to j
    Trail level of the move – proficiency of the move in the past
    Swarm Intelligence
    6
  • Application of ACO
    Scheduling Problem
    Vehicle Routing Problem
    Assignment Problem
    Set Problem
    Swarm Intelligence
    7
  • Particle Swarm Optimization
    ORIGINS:
    How can birds or fish exhibit such a coordinated and collective behavior?
    The study of the above mentioned problem accidentally revealed that PSO is an optimization technique.
    Swarm Intelligence
    8
  • Particle Swarm Optimization
    A computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality.
    Particle(candidate solution) improves its position based on 3 criteria:
    Inertia
    Personal Influence
    Social Influence
    Swarm Intelligence
    9
  • Particle Swarm Optimization
    For each particle     Initialize particleENDDo    For each particle         Calculate fitness value        If the fitness value is better than the best fitness value (pBest) in history            set current value as the new pBest    End    Choose the particle with the best fitness value of all the particles as the gBest    For each particle         Calculate particle velocity according to velocity equation.        Update particle position according to position equation.    End While maximum iterations or minimum error criteria is not attained
    Swarm Intelligence
    10
  • Particle Swarm Optimization
    Applications:
    Function Optimisation
    Optimal Control in Control Systems
    Swarm Intelligence
    11
  • Other Algorithms
    Cuckoo Search
    Intelligent Water Drops
    River Formation Dynamics
    Firefly Algorithm
    12
    Swarm Intelligence
  • Application of Swarm Intelligence
    Crowd Simulation
    Movies
    Lord of the Rings (Massive technology)
    Batman Returns (Simulation of bats)
    Airlines – Passenger Simulation
    Telecom Network
    Airport Gates
    Process Optimization
    13
    Swarm Intelligence
  • Pop Culture
    Prey – Michael Crichton
    Allucination – Isaac Asimov
    Matrix (movie)
    Mass Effect (video game)
    14
    Swarm Intelligence