Heuristics
Heuristics are problem-solving techniques or mental shortcuts that provide approximate solutions to complex problems when exact methods are impractical, too slow, or impossible. They are commonly used in computer science, artificial intelligence, and optimization to find good-enough solutions efficiently, often trading optimality for speed and simplicity. Examples include greedy algorithms, A* search, and rule-of-thumb approaches in decision-making.
Developers should learn heuristics when dealing with NP-hard problems, large-scale optimization, or real-time systems where exhaustive search is infeasible, such as in pathfinding, scheduling, or machine learning hyperparameter tuning. They are essential in AI for game playing, robotics, and data analysis, enabling practical solutions in resource-constrained environments by reducing computational complexity.