Minesweeper ~ app icon

Minesweeper ~

by Yi Zeng

Trending upSentimenttrend not available
Appeye score 82 out of 100, from 568 reviews (high confidence)

568 reviews analysed · 30 Jun 2020 – 24 Sep 2026 · scored 28 Sep 2026

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Based on 568 reviews from 30 Jun 2020 - 24 Sept 2026.

Overview

Appeye score
82/100high confidence
Category rank
#7400 of 18,828Games
Reviews analysed
568Scored reviews from the App Store.
Sentiment trend
Trending upIts trend signals are moving in a positive direction.
App Store
4.6

8.3K ratings

Review sentiment

71
App nameMinesweeper ~
SellerYi Zeng
GenreGames
Version9.2
Content rating4+
Requires iOS16.0
Size45 MB
Released4 Jun 2020
Current version30 Aug 2023
View on App Store
App description

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

Sentiment over time

Calendar-month positive review share for the selected store view. Overall is review-weighted across stores; months with fewer than 10 reviews are left out.

Monthly positive review share
0%50%100%78%50%Sep 2022Dec 2025

Version history sentiment

Per-release positive review share for each app version that has at least 3 analysed reviews, oldest first — so you can see whether the last real release helped or hurt separately from the calendar-month trend.

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Version history · App Store

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