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CS162 Week 5

CS162 Week 5. Kyle Dewey. Overview. Assignment 2b pain points Assignment 3a. Assignment 2b Pain Points. Assignment 3a. Goal. Write a Minesweeper solver Given a board in some state, infer Which spaces must be mines Which spaces must be clear. Minesweeper.

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CS162 Week 5

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  1. CS162 Week 5 • Kyle Dewey

  2. Overview • Assignment 2b pain points • Assignment 3a

  3. Assignment 2b Pain Points

  4. Assignment 3a

  5. Goal • Write a Minesweeper solver • Given a board in some state, infer • Which spaces must be mines • Which spaces must be clear

  6. Minesweeper • Grid of initially unrevealed tiles • Revealing a tile exposes: • A mine • A blank space • A number stating how many mines are adjacent to the revealed tile

  7. Minesweeper

  8. Adjacency • Based on horizontal, vertical, and both diagonal axes Blue cells are adjacent to the red cell

  9. Adjacency • Based on horizontal, vertical, and both diagonal axes Blue cells are adjacent to the red cell

  10. Adjacency • Based on horizontal, vertical, and both diagonal axes Blue cells are adjacent to the red cell

  11. Adjacency • Based on horizontal, vertical, and both diagonal axes Blue cells are adjacent to the red cell

  12. Success/Failure • Success: all non-mine positions have been uncovered • Failure: a cell containing a mine was uncovered

  13. Utilizing Numbers • In certain cases, it is possible use revealed numbers to reason about mine positions

  14. Minesweeper as a CSP • CSP = constraint satisfaction problem • For every number N, it must be the case that the sum of the mines in all adjacent cells is equal to N

  15. Minesweeper as a CSP • CSP = constraint satisfaction problem • For every number N, it must be the case that the sum of the mines in all adjacent cells is equal to N 1 = ...

  16. Minesweeper as a CSP • CSP = constraint satisfaction problem • For every number N, it must be the case that the sum of the mines in all adjacent cells is equal to N 1 = 0 ...

  17. Minesweeper as a CSP • CSP = constraint satisfaction problem • For every number N, it must be the case that the sum of the mines in all adjacent cells is equal to N 1 = 0 + 0 ...

  18. Minesweeper as a CSP • CSP = constraint satisfaction problem • For every number N, it must be the case that the sum of the mines in all adjacent cells is equal to N 1 = 0 + 0 + 0 ...

  19. Minesweeper as a CSP • CSP = constraint satisfaction problem • For every number N, it must be the case that the sum of the mines in all adjacent cells is equal to N 1 = 0 + 0 + 0 + 0 ...

  20. Minesweeper as a CSP • CSP = constraint satisfaction problem • For every number N, it must be the case that the sum of the mines in all adjacent cells is equal to N 1 = 0 + 0 + 0 + 0 + 0 ...

  21. Minesweeper as a CSP • CSP = constraint satisfaction problem • For every number N, it must be the case that the sum of the mines in all adjacent cells is equal to N 1 = 0 + 0 + 0 + 0 + 0 + 0 ...

  22. Minesweeper as a CSP • CSP = constraint satisfaction problem • For every number N, it must be the case that the sum of the mines in all adjacent cells is equal to N 1 = 0 + 0 + 0 + 0 + 0 + 0 + 0 ...

  23. Minesweeper as a CSP • CSP = constraint satisfaction problem • For every number N, it must be the case that the sum of the mines in all adjacent cells is equal to N 1 = 0 + 0 + 0 + 0 + 0 + 0 + 0 + X

  24. Minesweeper as a CSP • CSP = constraint satisfaction problem • For every number N, it must be the case that the sum of the mines in all adjacent cells is equal to N 1 = 0 + 0 + 0 + 0 + 0 + 0 + 0 + X simplify X = 1 (the unknown spot has a mine)

  25. Minesweeper as a CSP • For each number, there is one equation • The equations collectively form a system of equations which can be solved to derive a solution

  26. Additional Constraints • Each unknown square can have a value of either 0 or 1 (no mine or mine) • The total number of mines in unknown squares + the total number of previously inferred mines = the predefined number of mines on the board

  27. In CLP • CLP = constraint logic programming • The aforementioned problem can be represented and solved directly with ease • We will provide template code which already performs most of the board manipulation • You must implement code to add constraints

  28. Template Code

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