Hill climbing is a mathematical optimization algorithm, which means its purpose is to find the best solution to a problem which has a (large) number of possible solutions. Explaining the algorithm (and optimization in general) is best done using an example. In the Travelling salesman problem, we have a salesman who needs to visit a number of cities exactly once, after which he returns to the first city. The distances between each pair of cities are known, and we need to find the shortest route. As you can imagine, there is (often) a large number of possible solutions (routes) to a specific Travelling salesman problem; the goal is to find the best (i.e. the shortest) solution.
🔗Important Links:
Artificial Intelligence Playlist: https://www.youtube.com/playlist?list=PL5-M_tYf311YXhOOv6Cy4YgnwTslHOH5_
Steepest Ascent Hill Climbing: https://www.youtube.com/watch?v=LQbBGpiw1Pc
Article Credit: https://towardsdatascience.com/how-to-implement-the-hill-climbing-algorithm-in-python-1c65c29469de
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