Greedy algorithms make locally optimal choices for a global solution from "summary" of Data Structures and Algorithms in Python by Michael T. Goodrich,Roberto Tamassia,Michael H. Goldwasser
Greedy algorithms are a class of algorithms for solving optimization problems that make a sequence of choices, each of which is the best choice locally at the time it is made. In other words, a greedy algorithm makes a series of choices that are each the most immediately beneficial at each decision point, with the hope that this will lead to a globally optimal solution. The key characteristic of a greedy algorithm is that once a decision is made, it is never reconsidered. The algorithm proceeds by making a series of choices, each based on the current state of the problem, without regard to how those choices will affect future decisions. At each step, a greedy algorithm selects the best available option without considering the consequences of that choice in the long term. This means that the algorithm may not always find the best possible solution to a problem, but it will find a solution that is locally optimal at each step. This can be an advantage in situations where finding the absolute best solution is impractical or computationally infeasible. Greedy algorithms are often used in situations where finding the best possible ...
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