Hill-climbing search is one of the key search algorithms used in Artificial Intelligence.
The idea behind this search is to look for points based on the current location. So, if we have a data point D with a certain number of values V, the way it works is to somehow look for better points based on small variations in the different values.
Life, as we know it, has an inherent complexity associated with it. It is made up of numerous intertwined and hierarchical complex adaptive systems (cas). These systems evolve and adapt at a massive scale. Ranging from the current outbreaks of various virii such as variants of Influenza, SARS, SARS-Covid-19 and others are inherently connected with a large number of life forms and species.
Recent advances in Artificial Intelligence have demonstrated the use of techniques and algorithms which are similar, even if in a very very light manner, to the complexities in the natural world. One of these very popular so-called evolutionary algorithms is the “Genetic algorithm” presented originally by the likes of Prof. John Holland (RIP). Here we present a brief overview of Genetic Algorithms.