Consider a scenario where you are tasked with finding the shortest path for a robot to navigate through a maze with obstacles. How would you adapt BFS to handle this situation effectively?
- Implement A* Algorithm
- Modify BFS to account for obstacles
- Use Depth-First Search (DFS)
- Utilize Dijkstra's Algorithm with a heuristic
Adapting BFS for a maze with obstacles can be done by incorporating a heuristic approach, similar to A* Algorithm. A* considers both the cost to reach a point and an estimate of the remaining distance to the goal. In the context of a maze, this modification helps BFS navigate efficiently around obstacles, making it more effective for pathfinding in complex environments compared to the traditional BFS approach.
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