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Conway's Game of Chess

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Conway's Game of Chess

Chess, but each square also follows the rules of Conway's Game of Life. Only your own pieces count as neighbours when deciding births/deaths. For births, an empty square must have 3 neighbours for 2 consecutive turns. For deaths, a piece must have <2 or >3 neighbours for 3 consecutive turns. This is a simple proof of concept I made with python and curses. You can play with a friend locally or over a socket connection. Controls: Arrow keys to move the cursor, enter/space to select and move a piece, u or backspace to undo a move, r to redo a move, q or escape to quit, s to perform a move with stockfish if installed (useless since it has no knowledge of this variant), any other key to unselect a currently selected piece.

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Actual performance

80points
21comments
Made the leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: cursor · Missing: mac, agents, macos
63%63% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
52%52% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit
23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
10%10% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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