AI Search Algorithm Visualizer — Informed & Uninformed

Search Algorithm Visualizer

Informed & uninformed search in AI

Algorithm

Problem settings

Heuristic

f(n) = g(n) + w·h(n). At w = 0 A* degenerates to uniform-cost search; w > 1 makes h inadmissible — faster, but the path may no longer be optimal.

Compare

Executes every algorithm on the current problem and tabulates nodes expanded, nodes generated, peak frontier and solution cost.

0 / 0
speed
readyPick an algorithm and press Play.

Statistics

Legend

Start Goal Frontier (open) Explored (closed) Expanding now Child being tested Solution path Backward frontier Wall High-cost cell

Pseudocode 


    


    

      
Frontier & explored set

      

        

          
Frontier 0

          

        

        

          
Explored 0

          

        

      

      

        

      

    

  






  How to read this / keyboard shortcuts
  

    
Keyboard: Space play/pause · ← → step · Home End jump · R re-run.

    
Grid editing: pick a tool, then click or drag on the grid. Right-click always erases back to empty floor.

    
g, h, f: g(n) is the cost of the best path found so far from the start to n; h(n) is the heuristic estimate of the remaining cost from n to the goal; f(n) = g(n) + h(n) estimates the total cost of a solution through n. Uninformed algorithms ignore h entirely — that is exactly what makes them uninformed.

    
A note on truncation: DFS, DLS, IDDFS and IDA* can generate an exponential number of nodes. The visualizer stops after a fixed budget and says so in the status bar rather than freezing your browser.