[Haskell-cafe] lazy A-star search
anton.kholomiov at gmail.com
Sun Oct 30 16:44:02 CET 2011
I'm misunderstanding astar. I've thought that 'whole route'-heuristic
will prevent algorithm from going in circles. The more you circle around
the more the whole route distance is. Thank you for showing this.
Here is an updated version. searchBy function contains a state.
State value accumulates visited nodes:
-- | Heuristic search. Nodes are visited from smaller to greater.
searchBy :: Ord b => (a -> b) -> (a -> a -> Ordering) -> Tree a -> [a]
searchBy f heur t = evalState (searchBy' f heur t) S.empty
searchBy' :: Ord b
=> (a -> b) -> (a -> a -> Ordering) -> Tree a -> State (S.Set b) [a]
searchBy' f heur (Node v ts) = get >>= phi
where phi visited
| S.member (f v) visited = return 
| otherwise =
put (S.insert (f v) visited) >>
(v :) . foldr (mergeBy heur)  <$>
mapM (searchBy' f heur) ts
I need to add function Ord b => (a -> b). It
converts tree nodes into visited nodes. I'm using it
for saving distance-values alongside with nodes
in astar algorithm.
In attachment you can find algorithm with your example.
2011/10/27 Ryan Ingram <ryani.spam at gmail.com>
> Also, this wasn't clear in my message, but the edges in the graph only go
> one way; towards the top/right; otherwise the best path is ABCDEHIJ :)
> On Thu, Oct 27, 2011 at 10:48 AM, Ryan Ingram <ryani.spam at gmail.com>wrote:
>> You're missing one of the key insights from A-star (and simple djikstra,
>> for that matter): once you visit a node, you don't have to visit it again.
>> Consider a 5x2 2d graph with these edge costs:
>> B 1 C 1 D 1 E 9 J
>> 1 1 1 1 1
>> A 2 F 2 G 2 H 2 I
>> with the start node being A, the target node being J, and the heuristic
>> being manhattan distance. Your search will always try to take the top
>> route, on every node along the bottom path, even though you visit every
>> node along the top route in your first try at reaching the goal. You need
>> a way to mark that a node is visited and remove it from future
>> consideration, or else you're wasting work.
>> A-star will visit the nodes in the order ABCDE FGHIJ; your algorithm
>> visits the nodes in the order ABCDE FCDE GDE HE IJ.
>> -- ryan
>> On Sat, Oct 22, 2011 at 5:28 AM, Anton Kholomiov <
>> anton.kholomiov at gmail.com> wrote:
>>> Recently I was looking for an A-star search algorithm. I've found a
>>> but I couldn't understand the code. Then I saw some blogposts but they
>>> were difficult to understand too. I thought about some easier solution
>>> relies on laziness. And I've come to this:
>>> Heuristic search is like depth-first search but solutions in sub-trees
>>> are concatenated with mergeBy function, that concatenates two
>>> list by specific order:
>>> module Search where
>>> import Control.Applicative
>>> import Data.Function(on)
>>> import Control.Arrow(second)
>>> import Data.Tree
>>> -- | Heuristic search. Nodes are visited from smaller to greater.
>>> searchBy :: (a -> a -> Ordering) -> Tree a -> [a]
>>> searchBy heur (Node v ts) =
>>> v : foldr (mergeBy heur)  (searchBy heur <$> ts)
>>> -- | Merge two lists. Elements concatenated in specified order.
>>> mergeBy :: (a -> a -> Ordering) -> [a] -> [a] -> [a]
>>> mergeBy _ a  = a
>>> mergeBy _  b = b
>>> mergeBy p (a:as) (b:bs)
>>> | a `p` b == LT = a : mergeBy p as (b:bs)
>>> | otherwise = b : mergeBy p bs (a:as)
>>> Now we can define specific heuristic search in terms of searchBy:
>>> -- | Heuristic is distance to goal.
>>> bestFirst :: Ord h => (a -> h) -> (a -> [a]) -> a -> [a]
>>> bestFirst dist alts =
>>> searchBy (compare `on` dist) . unfoldTree (\a -> (a, alts a))
>>> -- | A-star search.
>>> -- Heuristic is estimated length of whole path.
>>> astar :: (Ord h, Num h) => (a -> h) -> (a -> [(a, h)]) -> a -> [a]
>>> astar dist alts s0 = fmap fst $
>>> searchBy (compare `on` astarDist) $ unfoldTree gen (s0, 0)
>>> where astarDist (a, d) = dist a + d
>>> gen (a, d) = d `seq` ((a, d), second (+d) <$> alts a)
>>> I'm wondering is it effective enough?
>>> Haskell-Cafe mailing list
>>> Haskell-Cafe at haskell.org
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