Research any topic before you write.

Find related topics. | Discover entities. | See connections. | Build a topical map.

A* search algorithm: History, Applications & Science

A* (pronounced "A-star") is a graph traversal and pathfinding algorithm that is used in many fields of computer science due to its completeness, optimality, and optimal efficiency. Given a weighted graph, a source node and a goal node, the algorithm finds the shortest path (with respect to the given weights) from source to goal.

Language: English [EN]
Use the mouse wheel or two fingers (on touchscreens) to zoom in and out of the map.
100%
More settings
100% 100% 100% 100% 100%

A* search algorithm topic overview

The analysis highlights History, Applications and Science as prominent areas in the source structure around A* search algorithm.

Related topics
58
Source areas
7
Connected nodes
65
Extracted relationships
18
Concept neighborhoods
26
Bridge connections
65

What this topic covers Research coverage

Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.

Description · 18 topics
Overview · 18 topics
Variants · 9 topics
History · 4 topics
Relations to other algorithms · 4 topics
Applications · 3 topics
Complexity · 2 topics

Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.

Key facts & relationships

High-confidence facts extracted from structured source data. Use them as anchors for further research.

Class
Search algorithm
Complete
yes
Data structure
Graph
Optimal
yes
Worst-case performance
O ( | E | log ⁡ | V | ) = O ( b d ) {\displaystyle O(|E|\log |V|)=O(b^{d})}
Worst-case space complexity
O ( | V | ) = O ( b d ) {\displaystyle O(|V|)=O(b^{d})}

Explore all related topics Closing gaps

Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.

Overview

History

Description

Complexity

Applications

Relations to other algorithms

Variants

Advanced semantic analysis

Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.

How A* search algorithm connects Entity context

The extracted context around A* search algorithm shows recurring relationship patterns in the source. For example, A* search algorithm → Archived, Brian Grinstead, February, Hierarchical Path-Finding, HPA, JavaScript, Retrieved, Search Algorithm, Updated, Variation Another extracted example is A* search algorithm → Search algorithm. Use these groups to spot repeated connection types before inspecting the individual relationships.

A* search algorithm

Top relations

related to External links · 10
A* search algorithm → Archived, Brian Grinstead, February, Hierarchical Path-Finding, HPA, JavaScript, Retrieved, Search Algorithm, Updated, Variation
Class · 1
A* search algorithm → Search algorithm
Complete · 1
A* search algorithm → yes
Data structure · 1
A* search algorithm → Graph
Optimal · 1
A* search algorithm → yes
Worst-case performance · 1
A* search algorithm → O ( | E | log ⁡ | V | ) = O ( b d ) {\displaystyle O(|E|\log |V|)=O(b^{d})}
Worst-case space complexity · 1
A* search algorithm → O ( | V | ) = O ( b d ) {\displaystyle O(|V|)=O(b^{d})}

Important terminology

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

node algorithm heuristic path goal displaystyle search nodes optimal graph cost admissible textstyle consistent shortest function case distance start solution

A* search algorithm relationships Subject–Predicate–Object triples

TTTA extracted 18 structured relationships around A* search algorithm. Examples in this analysis include A* search algorithm → Class → Search algorithm and A* search algorithm → Complete → yes. The table shows each extracted connection, where it came from and its confidence.

SubjectPredicateObjectConfidenceSrc
A* search algorithmClassSearch algorithm1.00infobox
A* search algorithmCompleteyes1.00infobox
A* search algorithmData structureGraph1.00infobox
A* search algorithmOptimalyes1.00infobox
A* search algorithmWorst-case performanceO ( | E | log ⁡ | V | ) = O ( b d ) {\displaystyle O(|E|\log |V|)=O(b^{d})}1.00infobox
A* search algorithmWorst-case space complexityO ( | V | ) = O ( b d ) {\displaystyle O(|V|)=O(b^{d})}1.00infobox
video gamesinstance ofis often used for the common pathfinding problem in applications0.80text
but was originally designed as a general graph traversal algorithminstance ofis often used for the common pathfinding problem in applications0.80text
A* search algorithmrelated to External linksVariation0.60section
A* search algorithmrelated to External linksHierarchical Path-Finding0.60section
A* search algorithmrelated to External linksHPA0.60section
A* search algorithmrelated to External linksBrian Grinstead0.60section

Related concept clusters Concept neighborhoods

The concept neighborhoods around A* search algorithm bring nearby vocabulary together. In this analysis, examples include Search, Path and Graph. Use the clusters to find adjacent concepts and terminology that may deserve separate research.

  • A* search algorithm
    • Search
    • Path
    • Graph
    • Paths
    • Node
    • Optimal
    • Cost
    • Admissible
    • Displaystyle
    • Goal
    • Heuristic
    • Dijkstra's
  • a* search algorithm
    • Search
    • Path
    • Nodes
    • Dijkstra's
    • Graph
    • Paths
    • Node
    • Optimal
    • Cost
    • Admissible
    • Heuristic
    • Shortest
  • graph traversal
    • Search
    • Algorithms
    • Shortest
    • Path
    • Space
    • Better
    • Complexity
    • Goal
    • Cases
    • Performance
    • Cost
    • Optimality
  • algorithm
    • Search
    • Path
    • Nodes
    • Dijkstra's
    • Graph
    • Node
    • Optimal
    • Heuristic
    • Shortest
    • Case
    • Displaystyle
    • Goal
  • weighted graph
    • Search
    • Algorithms
    • Shortest
    • Path
    • Space
    • Better
    • Complexity
    • Goal
    • Cases
    • Performance
    • Cost
    • Optimality
  • node
    • Path
    • Displaystyle
    • Closed
    • Value
    • Cost
    • Start
    • Expanded
    • Number
    • Set
    • One
    • Distance
    • Heuristic
  • shortest path
    • Cost
    • Shortest
    • Distance
    • Solution
    • Search
    • Since
    • Heuristic
    • One
    • Paths
    • Start
    • Displaystyle
    • Consistent
  • dijkstra's algorithm
    • Search
    • Path
    • Nodes
    • Dijkstra's
    • Graph
    • Node
    • Optimal
    • Heuristic
    • Displaystyle
    • Shortest
    • Case
    • Goal

Connections between topic areas Semantic bridges

For A* search algorithm, one of the stronger structural bridges in this analysis connects A* search algorithm with Overview. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.

Min side: 3
A* search algorithm — Overview · splits 47 ⟂ 19
A* search algorithm — Description · splits 47 ⟂ 19
A* search algorithm — Variants · splits 56 ⟂ 10
A* search algorithm — History · splits 61 ⟂ 5
A* search algorithm — Relations to other algorithms · splits 61 ⟂ 5
A* search algorithm — Applications · splits 62 ⟂ 4
A* search algorithm — Complexity · splits 63 ⟂ 3

Map overview Semantic statistics

A* search algorithm

Nodes66
Edges65
Triples18
Avg. degree1.97
Density0.030303
Components1

Source & methodology

TTTA analyzes the structure around A* search algorithm to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Applications & Science, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.

Source: Wikipedia — A* search algorithm · EN edition · Analysis: TopicsToTalkAbout

For writers, content strategists, SEOs, marketers and creators — from quick topic research to advanced semantic analysis.