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Based on social interactions (locally shared
knowledge) that provides the basis for
unguided problem solving.
Efficiency is related to the degree of
connectedness of the network and the
number of interacting agents.
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Distributed, no central control
Limited communication
No explicit model of environment
Perception of the environment
Composed of many, alike individual agents.
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Ant colony optimization
River formation dynamics
Particle swarm optimization
Gravitational search algorithm
Intelligent water drops
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Developed by M.Dorgio in 1992
Heuristic optimization method inspired by the
observation of real ant colonies.
Based on how ants find the shortest path
to food source.
The behavior of ants is a kind of stochastic
distributed optimization behavior.
Ants are blind, deaf and dumb.
 So how do they find the shortest path to
food sources?
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◦ Based on PHEROMONES.
◦ They follow the deposits of pheromones and
form a trail.
◦ Other ants get attracted to this trail.
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Pheromones are volatile in nature.
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Each ant choose an action based on
◦ Random choice
◦ Pheromone mediated
They move by sensing previous ant not by
sensing the environment.
 Each ant collects info about local
environment and act concurrently and
independently.
 Stigmergy governs info exchange.
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Network routing
Travelling sales man problem
Vehicle routing
Assignment problems
Set problems