Heuristics

What Does Heuristics Mean?

Heuristics is an approach to problem-solving in which the objective is to produce a working solution within a reasonable time frame. Instead of looking for a perfect solution, heuristic strategies look for a quick solution that falls within an acceptable range of accuracy.

Heuristics are used in machine learning (ML) and artificial intelligence (AI) when it’s impractical to solve a particular problem with a step-by-step algorithm. Because a heuristic approach emphasizes speed over accuracy, it is often combined with optimization algorithms to improve results. Successive iterations are interdependent, and each level of a deep neural network decides which avenues to choose and discard, based on their proximity to the desired solution.

In this context, the term heuristic is sometimes used as a synonym for “short-cut” because this approach to problem-solving does not waste time on things that are not likely to produce acceptable results.

Techopedia Explains Heuristics

Heuristic methods use available data, rather than predefined solutions, to solve machine and human problems. Heuristic solutions are not necessarily provable or accurate, but they are usually good enough to solve small-scale issues that are part of a larger problem.

Heuristics vs. algorithms

An algorithm provides step-by-step instructions for how to solve a specific problem in a finite number of steps. The resulting outcome is predictable and can be reliably reproduced when using the same input.

In contrast, heuristic outcomes are simply educated guesses. Heuristic outcomes cannot be predicted or reproduced reliably.