heuristic search if we simply pick the next row in the sequence of rows so the search for the solution is only what column to place the next queen in to aide in forward checkingthe board can be represented as tuple(queen locationsavailable locationsthe first item in the tuple is the list of placed queens the second item of the tuple is the list of available locations on the board the forward checking can pick one of the available locations for the next row at this point all locations in the second part of the tuple that conflict with the choice of the next queen placement can be eliminated thus forward checking removes all the possible locations that are no longer viable given choice of placement for queen the hill climbing part of solving the -queens problem comes into play when the choice of which column to place queen is made the column chosen is the one that least constrains future choices like the knight' tourthe -queens problem benefits when the next choice made leaves the maximum number of choices later using this heuristicforward checkingand the simple selection of the next row in which to place queenit is possible to solve the -queens problem in reasonable amount of time one solution is shown in fig to reviewimplementing hill climbing requires the alternative choices at each step be sorted according to the heuristic before they are placed on the stack otherwisethe code is exactly the same as that of depth first search in some caseslike the knight' tour and the -queens problemany solution is an optimal solution butas noted above when searching mazehill climbing does not necessarily find an optimal solution wouldn' it be nice if we could combine breadth first search and hill climbing fig -queens solution this copy belongs to 'acha