AI algorithms are so called because they have an
organization inspired by biological processes. The diversity of algorithms
classified as AI is significant and they, effectively, seek to enhance the strategy
by optimizations and combinations.
The genetic algorithm, for example, has an ability to
explore the solutions more efficiently than traditional methods, avoiding bias
on the process of optimizing the system, for not having properly considered the
solutions.
There are also algorithms, genetic programming, which have
the ability to combine logic, such as blocks, assembling and reassembling a
puzzle at a level of complexity above an optimization strategy only.
The AI also has a fascination and power. His argument must
be backed by performance improvements. The application must be systematically
analyzed and validated properly. Given the peculiarities of each system, it´s
necessary to clarify possible sources of inaccuracies.
