What characterizes a greedy algorithm?

A greedy algorithm is characterized by its approach of building a solution incrementally, focusing on making the most advantageous local choice at each step with the hope that these local optimizations will lead to a global optimal solution. This means it selects the option that seems the best at the moment—often the one that offers the greatest immediate benefit or the most favorable outcome—without considering the broader implications or future consequences of that choice.

It contrasts with other problem-solving strategies such as exhaustive search, which evaluates every possible solution, or dynamic programming, which solves complex problems by breaking them down into simpler subproblems and storing their results to avoid redundant calculations. Greedy algorithms are often simpler and more efficient than these other methods, but they do not guarantee a globally optimal solution for all problems; they work best on certain types of problems where local optimal choices lead to a global optimum.