feat: q3 & fix: update visited list in DFS, BFS

search.py

@@ -88,7 +88,7 @@ def depthFirstSearch(problem: SearchProblem):
     curr_state = problem.getStartState()
     isGoal = problem.isGoalState(curr_state)
 
-    visited = set()
+    visited = set([curr_state])
     stack = util.Stack()
 
     while not isGoal:
@@ -96,7 +96,6 @@ def depthFirstSearch(problem: SearchProblem):
         successors = problem.getSuccessors(curr_state)
         for (state, direction, cost) in successors:
             if state not in visited:
-                visited.add(state)
                 stack.push({
                     'state': (state, direction, cost),
                     'actions': actions
@@ -108,6 +107,7 @@ def depthFirstSearch(problem: SearchProblem):
         else:
             obj = stack.pop()
             (curr_state, direction, cost) = obj['state']
+            visited.add(curr_state)
             actions = obj['actions'] + [ direction ]
             isGoal = problem.isGoalState(curr_state)
 
@@ -123,7 +123,7 @@ def breadthFirstSearch(problem: SearchProblem):
     curr_state = problem.getStartState()
     isGoal = problem.isGoalState(curr_state)
 
-    visited = set()
+    visited = set([curr_state])
     queue = util.Queue()
 
     while not isGoal:
@@ -152,7 +152,40 @@ def breadthFirstSearch(problem: SearchProblem):
 def uniformCostSearch(problem: SearchProblem):
     """Search the node of least total cost first."""
     "*** YOUR CODE HERE ***"
-    util.raiseNotDefined()
+    actions = []
+
+    curr_state = problem.getStartState()
+    isGoal = problem.isGoalState(curr_state)
+    costs = 0
+
+    visited = set([curr_state])
+    queue = util.PriorityQueue()
+
+    while not isGoal:
+        # push in the P Queue
+        successors = problem.getSuccessors(curr_state)
+        for (state, direction, cost) in successors:
+            if state not in visited:
+                queue.push({
+                    'state': (state, direction, cost),
+                    'actions': actions,
+                    'costs': costs
+                }, costs + cost)                # if visited this successor node, how much cost will the agent need
+
+        # check whether reachable
+        if queue.isEmpty():
+            return []
+        else:
+            obj = queue.pop()
+            (curr_state, direction, cost) = obj['state']
+            visited.add(curr_state)
+            actions = obj['actions'] + [ direction ]
+            costs = obj['costs'] + cost
+
+            isGoal = problem.isGoalState(curr_state)
+
+    return actions
+    
 
 def nullHeuristic(state, problem=None):
     """