Minesweeper vs Minesweeper ~

No ads. No distractions. Just classic Minesweeper, rebuilt for iPhone and iPad. Minesweeper brings the classic familiar logic puzzle to modern touch screens with intuitive controls, clean graphics, advanced algorithms, and the classic rules you expect: a safe first tap, flags, question marks, chording, and the original difficulty levels. Stuck? Use Hints that prioritize simple deductions so you can learn the logic instead of blindly guessing. Hit an unavoidable 50/50? Luck helps prevent forced guess losses when you choose one of the safest mathematically available squares. Made a mistake? Smart Undo lets you rewind a loss while shuffling hidden mines so the puzzle stays interesting. Features: • Classic Minesweeper rules and difficulty levels • Custom boards • Safe first tap • Flags, question marks, and chording • Hints that teach logical deductions • Luck for unavoidable guesses • Smart Undo after a loss • Statistics by difficulty • Winning streak, win rate, best time, and median time tracking • iPhone and iPad support • Mouse, trackpad, and Apple Pencil support • No ads or in app purchases. This is my gift to you :) How to play: Reveal every safe square without tapping a mine. Numbers show how many adjacent squares contain mines. Tap to reveal, press and hold to flag, and tap a completed number to open ("chord") nearby squares. Start a new board at any time with the smiley button. Built for classic Minesweeper players, speed solvers, logic puzzle fans, and anyone who wants a clean, fast puzzle game without ads. Having trouble or have a feature request? Contact me directly from the app.

Classic minesweeper game, redefined by AI. Our minesweeper game is one of its own kind in the market. We leverage AI technology to achieve various improvement on top of the classic minesweeper game. - Exercise your brain and logic reasoning skills - 4 difficulty options - Fun experiences to unlock and daily rewards to claim. - Classic minesweeper redefined by AI * Redefined by AI * 1. Model the minesweeper game as a Constraint Satisfaction Problem (CSP) [a] 2. Precompute the heuristic score for each valid move using multiple state-of-the-art algorithms [b], to yield a stack rank of 10 (or less) best moves. 3. Based on the heuristic difference between the optimal move and the actual move by the user, we use our pre-defined probability (non-uniform distribution) to control the mine position (by ad-hoc switching cells on the board). 4. At the end of the game, further tune the mine-switching probability using win/lose ratio as an input [c], to ensure a custom tailored gaming experience that’s challenging but not frustrating. References: [a] https://inst.eecs.berkeley.edu/~cs188/fa18/assets/slides/lec4/FA18_cs188_lecture4_CSPs_6pp.pdf [b] https://dash.harvard.edu/bitstream/handle/1/14398552/BECERRA-SENIORTHESIS-2015.pdf?sequence=1 [c] https://en.wikipedia.org/wiki/Reinforcement_learning