I'm making a game engine for a board game called Blockade and right now I'm trying to generate all legal moves in a position. The rules aren't exactly the same as the actual game and they don't really matter. The gist is: the board is a matrix and you move a pawn and place a wall every move.
In short, I have to find whether or not a valid path exists from every pawn to every goal after every potential legal move (imagine a pawn doesn't move and a wall is just placed), to rule out illegal moves. Or rather, if I simplify it to a subproblem, whether or not the removal of a few edges (placing a wall) removes all paths to a node.
Brute-forcing it would take O(k*n*m), where n and m are the board dimensions and k is the number of potential legal moves. Searching for a path (worst case; traversing most of the board) is very expensive, but I'm thinking with dynamic programming or some other idea/algorithm it can be done faster since the position is the same the wall placement just changes, or rather, in graph terms, the graph is the same which edges are removed is just changed. Any sort of optimization is welcome.
Edit:
To elaborate on the wall (blockade). A wall is two squares wide/tall (depending on whether it's horizontal or vertical) therefore it will usually remove at least four edges, eg:
p | r
q | t
In this 2x2 matrix, placing a wall in the middle (as shown) will remove jumping from and to:
p and t, q and r, p and r, and q and t
I apologize ahead of time if I don't fully understand your question as it is asked; there seems to be some tacit contextual knowledge you are hinting at in your question with respect to knowledge about how the blockade game works (which I am completely unfamiliar with.)
However, based on a quick scan on wikipedia about the rules of the game, and from what I gather from your question, my understanding is that you are effectively asking how to ensure that a move is legal. Based on what I understand, an illegal move is a wall/blockade placement that would make it impossible for any pawn to reach its goal state.
In this case, I believe a workable solution that would be fairly efficient would be as follows.
Define a path tree of a pawn to be a (possibly but not necessarily shortest) path tree from the pawn to each reachable position. The idea is, you want to maintain a path tree for every pawn so that it can be updated efficiently with every blockade placement. What is described in the previous sentence can be accomplished by observing and implementing the following:
Here are resources on the adoption algorithm that is critical to doing what is described efficiently:
Note reading the description of the adopton algorithm included in the last bullet point above would be most critical to understanding how to adopt orphaned portions of your path-tree efficiently.
In terms of efficiency of this approach, I believe on average you should expect on average
O(1)operations for each adopted edge, meaning this approach should take aboutO(k)time to compute wherekis the number of board states which you wish to compute for.Note, the pawn path tree should actually be a reverse directed tree rooted at the goal nodes, which will allow the computation to be done for all legal pawn placements given a blockade configuration.