chapter six

6 Swarm intelligence: Ants

 

In this chapter

  • Seeing and understanding the inspiration for swarm intelligence algorithms
  • Solving problems with swarm intelligence algorithms
  • Designing and implementing an ant colony optimization algorithm

What is swarm intelligence?

Swarm intelligence algorithms, much like the evolutionary algorithms discussed in chapter 5, are a family of nature-inspired algorithms. Whereas evolutionary algorithms mimic genetic reproduction, swarm intelligence mimics the collective behavior of animals. 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 that ACO algorithms can solve

Representing state: What do paths and ants look like?

The ACO algorithm life cycle

Set up pheromones

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 ACO algorithms