13

Natural Algorithms — GA, SA, ANN, TS

Objectives

After reading this chapter, you should understand:

  • Why do we need Natural Algorithms—Where traditional algorithm design strategies fail
  • Evolution
  • Mutation and its significance
  • Working of a Genetic Algorithm—Why they work, how do they differ from random search
  • Simulated Annealing—Principles and applicability
  • Artificial Neural Networks—Similarities and differences with Human Brain
  • Artificial Neural Networks—Types, principles and applicability

Any sufficient advanced technology is indistinguishable from magic.

—Arthur C. Clarke

No, I’m not interested in developing a powerful brain. All I’m after is just a mediocre brain, something like the President of the American Telephone and Telegraph ...

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