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Home/ Questions/Q 8690943
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Editorial Team
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Editorial Team
Asked: June 13, 20262026-06-13T00:00:54+00:00 2026-06-13T00:00:54+00:00

I’ve been experimenting with different ways of implementing depth first search. I’ve found a

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I’ve been experimenting with different ways of implementing depth first search. I’ve found a few working ways, but they involved some rather tedious dictionary work. I’ve developed a new idea using lists, but the actions this implementation returns don’t match the desired result. I’ll try to comment the code as clearly as I can:

start = problem.getStartState()            ## returns an (x, y) tuple
children = problem.getSuccessors(start)    ##returns the children of a parent node in ((start                  
                                           state), action, cost) format. 
stack = Stack()                            ##creates a Stack (LIFO) data structure
visited = []                               ##list of visited nodes
visited.append(start)
for child in children:
    stack.push((child, [], [], 0))         ##push children to fringe in the format of (child,
    while stack:                           ##path taken, actions taken, cost) 
        parent = stack.pop()
        node = parent[0]
        if parent[0] in visited: continue
        visited.append(parent[0])
        path = parent[1] + [node[0]]           ##assigns previous path/actions/cost to new 
        actions = parent[2] + [node[1]]        ##node, creating a cumulative, ordered list of
        print actions                          ##the path/actions and a cumulative cost
        cost = parent[3] + node[2]
        if problem.isGoalState(node[0]):
            print parent[2]
            return parent[2]                    ## returns list of actions 
        children = problem.getSuccessors(node[0])
        if children != []:
            for child in children:
                stack.push((child, path, actions, cost))   ##assigns cumulative lists to child

Anyone see where my problems might lie in this implementation? BTW, I know DFS is an inefficient algorithm for most cases. But once I get this implementation right, it should be able to cross over to other search algorithms by simply changing the data structure that stores the children of the parent node.

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  1. Editorial Team
    Editorial Team
    2026-06-13T00:00:55+00:00Added an answer on June 13, 2026 at 12:00 am

    CS188 pal 😀 It’s really hard to read your code here… all those indexes %)
    Use more variables and it’ll be more clear.
    My solution:

    def depthFirstSearch(problem):
        fringe = util.Stack()
        expanded = set()
        fringe.push((problem.getStartState(),[],0))
        
        while not fringe.isEmpty():
            curState, curMoves, curCost = fringe.pop()
            
            if(curState in expanded):
                continue
            
            expanded.add(curState)
            
            if problem.isGoalState(curState):
                return curMoves
            
            for state, direction, cost in problem.getSuccessors(curState):
                fringe.push((state, curMoves+[direction], curCost))
        return []
    

    I hope I don’t need to comment it. It’s easy to read 🙂
    Have a good day 😉

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