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currently we use manhattan distance as the heuristic:
defheuristic(a: CoordTup, b: CoordTup) ->float:
"""return manhattan distance between two points"""returnnp.abs(a[0] -b[0]) +np.abs(a[1] -b[1])
(see maze_dataset/maze/lattice_maze.py)
This works fine for acyclic mazes, but is non-deterministic for some cyclic ones (this is particularly visible for high-p percolation mazes).
Ideally, it would be nice to be able to specify a solution heuristic in the MazeDatasetConfig. This would require modifying a number of functions to accept such a parameter:
LatticeMaze.generate_random_path()
get_maze_with_solution()
_generate_maze_helper()
SolvedMaze.from_targeted_lattice_maze()
The text was updated successfully, but these errors were encountered:
currently we use manhattan distance as the heuristic:
(see
maze_dataset/maze/lattice_maze.py
)This works fine for acyclic mazes, but is non-deterministic for some cyclic ones (this is particularly visible for high-p percolation mazes).
Ideally, it would be nice to be able to specify a solution heuristic in the
MazeDatasetConfig
. This would require modifying a number of functions to accept such a parameter:LatticeMaze.generate_random_path()
get_maze_with_solution()
_generate_maze_helper()
SolvedMaze.from_targeted_lattice_maze()
The text was updated successfully, but these errors were encountered: