First, clarify the problem constraints and edge cases, then model the board and token movements. Recognize that tokens move independently but may block each other, so consider dynamic programming or greedy strategies to maximize coin collection.
Pro tip: Start by asking clarifying questions about the board size, token count, and whether tokens can share cells after moves. This shows attention to detail and helps avoid incorrect assumptions.
Ask about board size, number of tokens, coin distribution, and movement rules. Confirm if tokens can move multiple times and if coins are removed after collection.
Represent the board as an array and tokens as movable elements. Note that each move is exactly 3 cells right, and tokens cannot overlap or jump over each other.
Break the problem into independent token paths, but consider interactions due to blocking. Determine if the problem can be solved with dynamic programming over positions.
Propose a DP approach where state includes token positions and collected coins, or a greedy strategy if tokens don't interfere. Discuss time and space complexity.
Walk through a small example to verify the algorithm, checking edge cases like tokens at the end of the board or multiple tokens blocking each other.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.