How do I implement A* search in Swift?

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.

Example Implementation of A* Search in Swift

// 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 }

A* search algorithm pathfinding Swift heuristic

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