What distinguishes a heuristic algorithm from a brute force algorithm?

A brute force algorithm is characterized by its method of problem-solving through exhaustive search, meaning it explores all possible solutions until it finds the correct one. This can be effective for smaller problems or when the solution space is limited, as it guarantees finding the optimal solution as it evaluates every possible option.

In contrast, heuristic algorithms offer a different approach. They are designed to find solutions more quickly and efficiently, particularly when dealing with larger or more complex problems where exhaustive searching would be computationally infeasible. Heuristic methods typically provide good enough solutions within a reasonable time frame, but they do not guarantee optimality, which is a key distinction from brute force methods.

Additionally, while brute force algorithms systematically check all possibilities, heuristic algorithms rely on experience, rules of thumb, or approximative techniques to navigate the solution space more intelligently. This strategic approach often results in faster performance, but at the potential cost of not reaching the best possible solution every time.

Understanding these differences is crucial in deciding which algorithm to use based on the problem at hand, the size of the input, and the importance of finding an optimal versus a satisfactory solution.