Question
On an N x N chessboard a knight starts at cell (r, c) and makes exactly K moves, each chosen uniformly at random among the 8 knight moves (even if it would leave the board, in which case the knight falls off and stops). Return the probability the knight is still on the board after K moves, rounded to 6 decimals. 1 <= N <= 25, 0 <= K <= 100, 0 <= r,c < N.
knight_on_board(N: int, K: int, r: int, c: int) → float[3,2,0,0]out0.0625State your approach and its time/space complexity out loud before you optimize. Handle the edge cases (empty input, duplicates, overflow), and say why you chose this over the brute force. Green tests are the floor, not the grade.
Vibe coding: describe the solution in plain language (or narrate it) and the coach grades your approach. Generating runnable code from your description is coming next.