The A* search algorithm is an informed search algorithm that is used for pathfinding and graph traversal. It efficiently finds the shortest path from a start node to a goal node using a heuristic to guide its search.
In Swift, you can implement the A* search algorithm by utilizing data structures such as priority queues to manage nodes, and NSData or dictionaries to maintain the costs of traversing each path.
// A* search algorithm implementation in Swift
class Node {
var name: String
var neighbors: [Node]
var heuristicCost: Double
init(name: String, heuristicCost: Double) {
self.name = name
self.neighbors = []
self.heuristicCost = heuristicCost
}
}
func aStarSearch(start: Node, goal: Node) -> [Node]? {
var openSet: Set = [start]
var cameFrom: [Node: Node] = [:]
var gScore: [Node: Double] = [start: 0]
var fScore: [Node: Double] = [start: start.heuristicCost]
while !openSet.isEmpty {
let current = openSet.min { fScore[$0, default: Double.infinity] < fScore[$1, default: Double.infinity] }!
if current === goal {
var path: [Node] = []
var currentNode: Node? = current
while currentNode != nil {
path.append(currentNode!)
currentNode = cameFrom[currentNode!]
}
return path.reversed()
}
openSet.remove(current)
for neighbor in current.neighbors {
let tentativeGScore = gScore[current, default: Double.infinity] + 1 // Assuming the cost to move to neighbor is 1
if tentativeGScore < gScore[neighbor, default: Double.infinity] {
cameFrom[neighbor] = current
gScore[neighbor] = tentativeGScore
fScore[neighbor] = tentativeGScore + neighbor.heuristicCost
openSet.insert(neighbor)
}
}
}
return nil // Path not found
}
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