45 lines
1.2 KiB
Python
45 lines
1.2 KiB
Python
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# this graph to check the algorithm
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graph={
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'S':[('A',2),('B',3),('D',5)],
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'A':[('C',4)],
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'B':[('D',4)],
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'C':[('D',1),('G',2)],
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'D':[('G',5)],
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'G':[],
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}
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#to calculate the total cost of path
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def path_cost(path):
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total_cost=0
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for (node, cost) in path:
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total_cost+=cost
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return total_cost , path[-1][0]
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# well sort queue items based on total path
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#if two items have the same total_cost then sort by node name (alphabetically)
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# uniform cost search
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def UCS(graph, start, goal):
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visited=[]
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queue=[[(start,0)]]
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while queue:
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queue.sort(key=path_cost)#sorting by cost
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path=queue.pop(0)#choosing least cost
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node=path[-1][0]
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if node in visited:
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continue
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visited.append(node)
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if node==goal:
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return path
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else:
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adjacent_nodes=graph.get(node,[])
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for(node2,cost)in adjacent_nodes:
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new_path=path.copy()
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new_path.append((node2,cost))
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queue.append(new_path)
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solution= UCS(graph,'S','G')
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print('solution is ' , solution)
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print ('cost of solution is ',path_cost(solution)[0])
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