Answer:
Answer:
(a) To find the shortest path from Chongqing to Xiamen using Depth-First Search, we can use the following algorithm:
Start from the Chongqing node and mark it as visited
Visit one of its neighbors (say, Guilin) that has not been visited yet and mark it as visited
Repeat the above step for the new node (Guilin), visiting an unvisited neighbor (Wuhan)
Continue this process until the goal node (Xiamen) is reached or until all nodes have been visited
If the goal node is found, return the path from the start to the goal node. If no path is found, return "no path"
The intermediate search trees are shown below:
Search tree after visiting Chongqing: Chongqing
Search tree after visiting Guilin: Chongqing | Guilin
Search tree after visiting Wuhan: Chongqing | Guilin--Wuhan
Search tree after visiting Nanchang: Chongqing | Guilin--Wuhan | Nanchang
Search tree after visiting Xiamen (goal node): Chongqing | Guilin--Wuhan | Nanchang--Xiamen
So the shortest path from Chongqing to Xiamen using Depth-First Search is: Chongqing -> Guilin -> Wuhan -> Nanchang -> Xiamen.
(b) To find the shortest path from Guangzhou to Wuhan using Recursive Best-First Search, we can use the following algorithm:
Start from the Guangzhou node and calculate the heuristic value (estimated distance) to the goal node (Wuhan)
Add the start node to the open list and mark it as visited
While the open list is not empty:
Get the node with the lowest f-value (heuristic + actual distance) from the open list
If this node is the goal node, return the path from the start to the goal node
Otherwise, expand the node by generating its unvisited neighbors and calculating their f-values
Add these neighbors to the open list and mark them as visited
Update the f-values of any neighbors already on the open list if a better path is found
The intermediate search trees are shown below:
Search tree after visiting Guangzhou: Guangzhou
Search tree after visiting Wuhan (goal node): Guangzhou--Wuhan
So the shortest path from
Step-by-step explanation: