Struggles with A* Search Algorithm in C# - Heuristic Not Returning Optimal Path
I'm updating my dependencies and I'm following best practices but I've been banging my head against this for hours. I'm stuck on something that should probably be simple. I'm currently implementing the A* search algorithm in C# for a grid-based pathfinding application. However, I'm working with issues where the algorithm occasionally returns a suboptimal path, even though I believe my heuristic function is designed correctly. I am using a simple Euclidean distance heuristic, and the search seems to get exploring in certain configurations, particularly when the grid has obstacles placed in a specific arrangement. Here’s a snippet of my A* implementation: ```csharp public List<Node> AStar(Node start, Node goal) { var openSet = new HashSet<Node> { start }; var cameFrom = new Dictionary<Node, Node>(); var gScore = new Dictionary<Node, float>(); var fScore = new Dictionary<Node, float>(); foreach (var node in allNodes) { gScore[node] = float.MaxValue; fScore[node] = float.MaxValue; } gScore[start] = 0; fScore[start] = Heuristic(start, goal); while (openSet.Count > 0) { var current = openSet.OrderBy(n => fScore[n]).First(); if (current.Equals(goal)) return ReconstructPath(cameFrom, current); openSet.Remove(current); foreach (var neighbor in GetNeighbors(current)) { if (!openSet.Contains(neighbor)) continue; float tentativeGScore = gScore[current] + Cost(current, neighbor); if (tentativeGScore < gScore[neighbor]) { cameFrom[neighbor] = current; gScore[neighbor] = tentativeGScore; fScore[neighbor] = gScore[neighbor] + Heuristic(neighbor, goal); } } } return new List<Node>(); // Return empty if no path is found } private float Heuristic(Node a, Node b) { return (float)Math.Sqrt(Math.Pow(a.X - b.X, 2) + Math.Pow(a.Y - b.Y, 2)); } ``` While debugging, I noticed that if I place obstacles in the middle of the grid, the algorithm tends to favor paths that are longer due to how the heuristic is calculated. I've tried adjusting the heuristic weight but it seems to only slightly improve the results. I also verified that the neighbor nodes are correctly identified and updated. Does anyone have insights on how I can refine the heuristic or restructure the search algorithm to avoid these suboptimal paths? Any suggestions on debugging techniques for this kind of algorithm would also be appreciated! I'm on Linux using the latest version of C#. Is there a simpler solution I'm overlooking? I've been using C# for about a year now. Any suggestions would be helpful.