I started with the standard get_neighbors and that part was fine.
First, clarify the problem: gates override normal movement, so neighbor generation must check the current cell's type. Then, modify the neighbor function to return only the forced direction if the current cell is a gate, otherwise the standard four directions. Finally, argue that BFS/DFS remains correct because the state space is still a graph and the search explores all reachable states.
Pro tip: Emphasize that the key is to treat gates as deterministic transitions, and that the search algorithm itself doesn't need to change—only the graph definition does. This shows you understand the separation of concerns between graph representation and search.
Restate the problem: gates force a single move, overriding normal 4-directional expansion. Confirm that gates are cells with directional markers (e.g., '>', '<', '^', 'v') and that the traveler must move in that direction if possible.
In the neighbor function, first check if the current cell is a gate. If so, return only the forced neighbor (if within bounds and not a wall). Otherwise, return the standard four neighbors.
Explain that BFS/DFS operate on the graph defined by the neighbor function, so no changes to the search algorithm are needed. The search will naturally follow forced moves.
Argue that the modified neighbor function still defines a valid graph (directed edges). BFS/DFS will explore all reachable states and find a path if one exists, because they are complete for finite graphs.
Mention edge cases: gate at boundary, gate pointing to a wall, cycles created by gates. Discuss that gates may reduce branching, potentially improving performance, but could also create dead ends.
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