Blog
-- Thoughts on data analysis, software
development and innovation management. Comments are welcome
Post 75
Foraging ants as living particle filters
24-Feb-2013
Ant colonies are admirable examples of cooperative societies. Some of its
members are prepared to build their complex lairs, some others constitute
an army to protect their population, some others explore the outer world
and gather food, etc. With respect to the latter function, which
to me is the most representative of ant colony behaviour, I coded a simple
simulation in JavaScript
inspired by the js1k competition
(demo and
code available here).
The ants in the app have been implemented following a state machine.
Initially, they forage for food, drawing a random walk while they operate
in this searching-state. Once they find a source of nurture, the ants
transit to another state where they return home, leaving a
pheromone trail behind for others to follow. Finally, they end up in a loop
going back and forth collecting more food. And as time goes by, more and
more ants flock to the food-fetching loop. Therefore, they get the job done
more rapidly and minimise the danger of an outer menace.
In a sense, foraging ants remind me of a particle filter where the
particles are living beings moving stochastically to reach some objective.
Thus, their behaviour could be cast as a biologically-inspired search
algorithm for an optimisation procedure, considering that the objective
is a cost function to be minimised.
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