Grokking Artificial Intelligence Algorithms by Rishal Hurbans

Author:Rishal Hurbans [Hurbans, Rishal]
Language: eng
Format: epub, pdf
Publisher: Manning Publications Co.
Published: 0101-01-01T00:00:00+00:00

Determine the stopping criteria

The algorithm stops after several iterations: conceptually, the number of tours that the group of ants concludes. Ten iterations means that each ant does 10 tours; each ant would visit each attraction once and do that 10 times (figure 6.28).

7. The algorithm can’t continue indefinitely. By creating stopping criteria, the algorithm converges to good solutions without unnecessary iterations.

Figure 6.28 Reached stopping condition?

The stopping criteria for the ant colony optimization algorithm can differ based on the domain of the problem being solved. In some cases, realistic limits are known, and when they’re unknown, the following options are available:

Stop when a predefined number of iterations is reached. In this scenario, we define a total number of iterations for which the algorithm will always run. If 100 iterations are defined, each ant completes 100 tours before the algorithm terminates.

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