[AI] (Tech Dose of the Day) Particle Swarm Optimization

vishnu ramchandani vishnuhappy at yahoo.com
Mon Feb 11 23:05:54 EST 2008


PSO (Particle Swarm Optimization )
contributor : Media&Entertainment Delivery Group
(MphasiS Software Services)
What is PSO?
Particle Swarm Optimization is a stochastic,
population-based evolutionary computer algorithm for
problem solving. It is a kind of swarm intelligence
that is based on social-psychological principles and
provides insights into social behavior, as well as
contributing to engineering applications.
Further Info:
The particle swarm optimization algorithm was first
described in 1995 by James Kennedy and Russell C.
Eberhart. The techniques have evolved greatly since
then, and the original version of the algorithm is
barely recognizable in the current ones.
Social influence and social learning enable a person
to maintain cognitive consistency. People solve
problems by talking with other people about them, and
as they interact their beliefs, attitudes, and
behaviors change; the changes could typically be
depicted as the individuals moving toward one another
in a sociocognitive space.
The particle swarm simulates this kind of social
optimization. A problem is given, and some way to
evaluate a proposed solution to it exists in the form
of a fitness function. A communication structure or
social network is also defined, assigning neighbors
for each individual to interact with. Then a
population of individuals defined as random guesses at
the problem solutions is initialized. These
individuals are candidate solutions. They are also
known as the particles, hence the name particle swarm.
An iterative process to improve these candidate
solutions is set in motion. The particles iteratively
evaluate the fitness of the candidate solutions and
remember the location where they had their best
success. The individual's best solution is called the
particle best or the local best. Each particle makes
this information available to their neighbors. They
are also able to see where their neighbors have had
success. Movements through the search space are guided
by these successes, with the population usually
converging, by the end of a trial, on a problem
solution better than that of non-swarm approach using
the same methods.
Further References
wikipedia : 
http://en.wikipedia.org/wiki/Particle_swarm_optimization
swarm intelligence : 
http://www.swarmintelligence.org/
http://www.cis.syr.edu/~mohan/pso/  


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