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In recent years, the emergence of the first quantum computers at a time whenAI is undergoing a fruitful era has led many AI researchers to be tempted intoadapting their algorithms to run on a quantum computer. However, in many casesthe initial enthusiasm has ended in frustration, since the features andprinciples underlying quantum computing are very different from traditionalcomputers. In this paper, we present a discussion of the difficulties arisingwhen designing a quantum version of an evolutionary algorithm based on Darwin'sevolutionary mechanism, the so-called genetic algorithms. The paper includesthe code in both Python and QISKIT of the quantum version of one of theseevolutionary algorithms allowing the reader to experience the setbacks arisingwhen translating a classical algorithm to its quantum version. The algorithmstudied in this paper, termed RQGA (Reduced Quantum Genetic Algorithm), hasbeen chosen as an example that clearly shows these difficulties, which arecommon to other AI algorithms.

The Conquest of Quantum Genetic Algorithms: The Adventure to Cross the Valley of Death