Ma

MazeBall [not mobile friendly; sorry]

Hacker News

MazeBall [not mobile friendly; sorry]

A colleague provided a maze-solving challenge that I reduced to a game that can be played at the following link: https://ryan-duve.github.io/mazeball.html The challenge is to find the shortest sequence of moves to get all the red balls to the green square, as well as an algorithm to generate that sequence. I made the game to guide my intuition and solved it in 188 moves just by eyeballing[1], but I am confident there are considerable gains to be made. Warning : Javascript is not my primary language, and I have no idea how to make a good webapp. As a result, this is hugely unoptimized and probably unplayable on mobile despite my best Stack Overflow efforts and timeboxing the whole thing to this afternoon. If Javascript is your cup of tea and you are interested in helping improve this, drop me a message on Github[2]. Take a look, have fun and let me know if you come up with a cool solution. [1] [see comment for long link] [2] https://github.com/ryan-duve/maze_ball

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Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
82%82% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
AppSumoMay struggle as an AppSumo deal · Strong signals: friendly · Missing: plus, platform, intuitive
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
37%37% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
33%33% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
12%12% 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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