PathfindingD2Phase 1heuristicgridshortest-path

A* Search

Heuristic-driven shortest path search balancing speed and optimality.

Easy Explanation

A* uses distance-so-far plus a heuristic guess to focus search toward the goal while still finding optimal paths.

Renderer Mode

`Simple` uses abstract, short-form-friendly visuals. `Advanced` keeps the current detailed view.

Arrays + Grid
Visualizer
O(V^2 + E)A*
Heuristic-guided weighted-grid search with open-set selection and score updates.

Grid

n/a

Expanded

0

Distance

n/a

Result

Searching

Safe mode: choose a tool to edit the grid.

Ready

Press Play or Step to start execution.

No A* run available for visualization.
Legend: S/T start/target, # blocked, cyan=open set, blue=closed set, violet ring = heavy, lime ring = weight override, g = cost from start, h = estimated cost to target, f = g+ h (A* priority).
A* Search Implementation
Pseudocode + TypeScript
Reference implementation examples are intentionally abstracted from the playback engine so learners can map concepts to code.
pseudocode
function a_star(graph, start, target, heuristic):
  open_set <- { start }
  g[start] <- 0
  f[start] <- heuristic(start, target)
  parent <- empty

  while open_set is not empty:
    node <- open_set node with lowest f
    remove node from open_set

    if node == target:
      return g[target], reconstruct_path(parent, target)

    for each (neighbor, weight) in edges(node):
      candidate_g <- g[node] + weight
      if candidate_g < g[neighbor]:
        parent[neighbor] <- node
        g[neighbor] <- candidate_g
        f[neighbor] <- candidate_g + heuristic(neighbor, target)
        add neighbor to open_set

  return not found
1.00xNo Run