6 Swarm intelligence: Ants

 

This chapter covers

  • Seeing and understanding what inspired swarm intelligence algorithms
  • Solving problems with swarm intelligence algorithms
  • Designing and implementing an ant colony optimization algorithm

What is swarm intelligence?

Swarm intelligence algorithms are a subset of evolutionary algorithms that were discussed in chapter 5 and are also known as nature-inspired algorithms. As with the theory of evolution, the observation of the behavior of life forms in nature is the inspiration for the concepts behind swarm intelligence. When we observe the world around us, we see many life forms that are seemingly primitive and unintelligent as individuals, yet exhibit intelligent emergent behavior when acting in groups.

Problems applicable to ant colony optimization

Representing state: What do paths and ants look like?

The ant colony optimization algorithm life cycle

Initialize the pheromone trails

Set up the population of ants

Choose the next visit for each ant

Update the pheromone trails

Update the best solution

Determine the stopping criteria

Use cases for ant colony optimization algorithms

Summary of ant colony optimization