A heuristic function ranks alternatives, in search algorithms, at each branching step based on the available information to decide which branch to follow.

A heuristic function, in the context of artificial intelligence and search algorithms, is a function that estimates the cost of reaching the goal from a given state in a problem-solving task. It provides a rule or guideline for making informed decisions when navigating through a search space, typically in the context of search algorithms like A* (A-star).

The purpose of a heuristic function is to guide the search process towards the most promising paths by providing an estimate of the remaining cost or distance to the goal from any given state. This estimate doesn’t necessarily need to be exact but should be admissible, meaning it never overestimates the true cost to reach the goal. Heuristic functions are crucial in optimizing search algorithms, allowing them to efficiently explore the search space and find solutions more quickly.

In summary, a heuristic function aids in decision-making during the search process by providing an estimated cost to reach the goal, helping algorithms focus on the most promising paths first.