Search Algorithms

An admissible heuristic is a function used in search algorithms that never overestimates the cost of reaching a goal.

Beam Search is a heuristic search algorithm used in AI for finding the most promising solutions among many options.

Bidirectional Search is an AI search algorithm that simultaneously explores paths from both the initial state and the goal state.

Blind Search is an algorithmic approach that explores solution spaces without domain knowledge.

BM25 is a ranking function used by search engines to evaluate the relevance of documents to a query.

A consistent heuristic ensures that the estimated cost to reach a goal never exceeds the actual cost from any point.

Exhaustive search is an algorithmic approach that systematically explores all possible solutions to find the optimal one.

Greedy Search is an optimization algorithm that makes locally optimal choices at each step to find a solution.

Informed search employs knowledge about the problem to find solutions more efficiently than uninformed methods.

Informed Search Algorithms utilize domain knowledge to enhance search efficiency in problem-solving.

Iterative Deepening combines depth-first and breadth-first search strategies to efficiently explore search trees.

Iterative Deepening Search is a search algorithm combining depth-first and breadth-first search strategies to find optimal solutions.

Optimal Search refers to algorithms designed to efficiently find solutions or information in large datasets or search spaces.

Path Search is an algorithmic technique used to find the optimal route between nodes in a graph or network.