In this article Best First Search Algorithm Learn Best First Search (Heuristic Search) with definition, algorithm steps, heuristic function, example, advantages, limitations, and applications.
Best First Search Algorithm:
Best First Search (Heuristic Search)
Introduction
- Best First Search is an Informed Search (Heuristic Search) technique.
- The search begins with the node that appears closest to the goal, based on a heuristic function h(n).
- Unlike BFS/DFS, it guides the search toward the goal, exploring fewer nodes.
Diagram: Concept of Best First Search
Start → Select node with lowest h(n) → Expand → Add children to queue → Repeat → Goal
Heuristic Function (h(n))
- h(n) = Estimated cost or distance from node n to the goal.
- Node with the lowest h(n) is expanded first.
- Examples:
- Straight-line distance
- Manhattan distance
Working Principle
- Place the starting node in a priority queue.
- At each step, expand the node with the lowest heuristic value.
- Add its successors to the queue with their heuristic values.
- Repeat until the goal node is found.
Flowchart: Best First Search
Start → Insert Start Node into Priority Queue
↓
Is Queue Empty?
↓ No
Remove Node with Lowest h(n) → Is Goal?
↓ No → Add Unvisited Children to Queue → Repeat
↓ Yes → Goal Found → Stop
Algorithm (Steps)
- Insert the starting node into the priority queue.
- Remove the node with the lowest h(n) from the queue.
- If the node is the goal, stop.
- Otherwise, add its child nodes to the queue with their heuristic values.
- Repeat until the queue is empty or the goal is found.
Example
Tree Structure with Heuristic Values:
A(6)
/ \
B(4) C(2)
/ \
D(1) E(3)
Traversal Order:
A → C → E → B → D
Node selection is based on the lowest heuristic value h(n) at each step.
Time and Space Complexity
| Complexity | Formula |
| Time | O(b^m) (Worst case) |
| Space | O(b^m) |
Where:
- b = branching factor
- m = maximum depth
Characteristics of Best First Search
- Heuristic-based search
- Faster than BFS and DFS
- Not guaranteed optimal
- Requires more memory
Advantages of Best First Search
- Explores fewer nodes than uninformed search
- Provides faster solutions
- Goal-oriented
Limitations of Best First Search
- Does not guarantee the optimal solution
- Wrong heuristic → may follow incorrect paths
- Can get stuck in local minima
Applications of Best First Search
- Path-finding problems
- Games AI (e.g., Chess, 8-puzzle)
- Scheduling
- Route planning
Conclusion
- Best First Search is an effective heuristic-based search technique.
- Fast and goal-directed, but does not always give the lowest-cost solution.
- Forms the basis for more advanced algorithms like A Search*.
Some More:
- POP- Introduction to Programming Using ‘C’
- DS – Data structure Using C
- OOP – Object Oriented Programming
- Java Programming
- DBMS – Database Management System
- RDBMS – Relational Database Management System
- https://defineinfoloop.blogspot.com/?m=1