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A graph search strategy that expands the most promising node first according to a heuristic evaluation.
DESCRIPTION
Best-first search explores nodes in order of heuristic desirability using a priority queue. Greedy best-first uses only the estimated cost-to-go, while A* augments with the path cost for optimality under admissible heuristics. It’s effective for pathfinding and planning but may get trapped by misleading heuristics. Performance depends on heuristic quality and tie-breaking strategy. Memory consumption can be high due to frontier storage.
ALTERNATIVE DEFINITIONS
Wikipedia
Best-first search is a search algorithm which explores a graph by expanding the most promising node chosen according to a specified rule.
Defines selection by a rule, typically a heuristic evaluation.
MIT OpenCourseWare
Best-first strategies rank alternatives and choose the one that appears best according to a heuristic, revising choices as new information appears.
Highlights dynamic re-ranking and heuristic-driven exploration.
RELATED TERMS
Greedy Decoding Heuristic Priority Queue Graph Search Dijkstra’s Algorithm Beam Search Breadth-First Search Depth-First Search
COMPETING TERMS
A-star Search Uniform-Cost Search
RELATIONS
- Broader: Search
- Narrower: A-star Search Beam Search
KNOWLEDGE AREAS
AI Software Engineering Mathematics
TARGET AUDIENCE
AI Engineer Software Developer Data Scientist
EXTERNAL SOURCES
- Wikipedia - Best-first search
- Stanford CS221 - Lecture on search and heuristics
- Red Blob Games - Visual guide to A* search
TOP QUESTIONS
How does Best-First Search differ from A* Search?
Greedy best-first uses only the heuristic cost-to-go, while A* combines path cost and heuristic, achieving optimality with admissible heuristics.
Category: Alternatives
When should I use Best-First Search?
Use it when a good heuristic exists and you need fast, approximate solutions in large search spaces.
Category: Requirements
What are common pitfalls with Best-First Search?
Poor heuristics cause excessive exploration or dead-ends; memory usage can grow quickly with large frontiers.
Category: Mistakes
How do I choose a heuristic for Best-First Search?
Heuristics should be informative, cheap to compute, and, for A*, admissible and consistent to ensure optimality.
Category: Requirements
What data structure supports Best-First Search?
A priority queue (min-heap) orders nodes by heuristic evaluation.
Category: Example
Is Best-First Search complete?
Greedy best-first is not necessarily complete, especially with infinite spaces; A* can be complete under certain conditions.
Category: Misunderstanding
What’s a hot topic around Best-First Search?
Learning heuristics from data for planning and pathfinding is an active area.
Category: Topic
How do tie-breaking strategies affect performance?
They influence node ordering and can reduce search churn or improve path quality in practice.
Category: Management
What are real-world applications of Best-First Search?
Robot pathfinding, game AI navigation, and route planning systems often rely on best-first strategies.
Category: Example