Add UCS and A*

search.py

@@ -100,10 +100,10 @@ def depthFirstSearch(problem: SearchProblem) -> List[Directions]:
         currNode, paths = st.pop()
         if problem.isGoalState(currNode):
             return paths
-        if not vis.__contains__(currNode):
+        if currNode not in vis:
             vis.add(currNode)
             for nextNode, path, _ in problem.getSuccessors(currNode):
-                if not vis.__contains__(nextNode):
+                if nextNode not in vis:
                     st.push((nextNode, paths + [path]))
     return []
 
@@ -119,10 +119,10 @@ def breadthFirstSearch(problem: SearchProblem) -> List[Directions]:
         currNode, paths = q.pop()
         if problem.isGoalState(currNode):
             return paths
-        if not vis.__contains__(currNode):
+        if currNode not in vis:
             vis.add(currNode)
             for nextNode, path, _ in problem.getSuccessors(currNode):
-                if not vis.__contains__(nextNode):
+                if nextNode not in vis:
                     q.push((nextNode, paths + [path]))
     return []
 
@@ -130,7 +130,26 @@ def breadthFirstSearch(problem: SearchProblem) -> List[Directions]:
 def uniformCostSearch(problem: SearchProblem) -> List[Directions]:
     """Search the node of least total cost first."""
     "*** YOUR CODE HERE ***"
-    util.raiseNotDefined()
+    pq: util.PriorityQueue = util.PriorityQueue()
+    vis: set = set()
+    pq.push(
+        item=(problem.getStartState(), [], 0), priority=0
+    )  # item: state, paths, cost; priority: priority
+
+    while not pq.isEmpty():
+        currNode, paths, cost = pq.pop()
+        if problem.isGoalState(currNode):
+            return paths
+        if currNode not in vis:
+            vis.add(currNode)
+            for nextNode, path, stepCost in problem.getSuccessors(currNode):
+                if nextNode not in vis:
+                    pq.push(
+                        item=(nextNode, paths + [path], cost + stepCost),
+                        priority=cost + stepCost,
+                    )
+    return []
+
 
 def nullHeuristic(state, problem=None) -> float:
     """
@@ -142,7 +161,28 @@ def nullHeuristic(state, problem=None) -> float:
 def aStarSearch(problem: SearchProblem, heuristic=nullHeuristic) -> List[Directions]:
     """Search the node that has the lowest combined cost and heuristic first."""
     "*** YOUR CODE HERE ***"
-    util.raiseNotDefined()
+
+    def priorityFunction(item):
+        state, path, g = item
+        return g + heuristic(state, problem)
+
+    pqwf: util.PriorityQueueWithFunction = util.PriorityQueueWithFunction(
+        priorityFunction
+    )
+    vis: set = set()
+    pqwf.push((problem.getStartState(), [], 0))
+
+    while not pqwf.isEmpty():
+        currNode, paths, cost = pqwf.pop()
+        if problem.isGoalState(currNode):
+            return paths
+        if currNode not in vis:
+            vis.add(currNode)
+            for nextNode, path, stepCost in problem.getSuccessors(currNode):
+                if nextNode not in vis:
+                    pqwf.push((nextNode, paths + [path], cost + stepCost))
+    return []
+
 
 # Abbreviations
 bfs = breadthFirstSearch