XO Challenge Взлом 1.0
Разработчик: Adolfo Vera Blasco
Категория: Игры
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Описание
Now you can play Tic Tac Toe on your iPhone or iPod Touch for free.
In XO Challenge you will play against a Machine Learning model living in your iPhone. This ensures that your iPhone won't keep making the same moves over and over again.
XO Challenge offers a new game mode in a In-App purchase
* Times Up! game mode. You only have 1, 3 or 5 seconds to think your next move
Behind The Scenes
XO Challenge was born during the time I was writing a serie of articles about Core ML and Create ML, part of Apple technologies related to Machine Learning (aka ML).
Would be possible that a ML model "learn" to play an simple strategy game and even defeat a human player?
Well, the answer is a download far from you.
Enjoy!
The articles serie...
http://desappstre.com/category/machine-learning/create-ml/
Thanks to UCI to mantain one of the best ML models repository. The model used in this app could be found at...
https://archive.ics.uci.edu/ml/datasets/Tic-Tac-Toe+Endgame
Dua, D. and Graff, C. (2019). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science.
In XO Challenge you will play against a Machine Learning model living in your iPhone. This ensures that your iPhone won't keep making the same moves over and over again.
XO Challenge offers a new game mode in a In-App purchase
* Times Up! game mode. You only have 1, 3 or 5 seconds to think your next move
Behind The Scenes
XO Challenge was born during the time I was writing a serie of articles about Core ML and Create ML, part of Apple technologies related to Machine Learning (aka ML).
Would be possible that a ML model "learn" to play an simple strategy game and even defeat a human player?
Well, the answer is a download far from you.
Enjoy!
The articles serie...
http://desappstre.com/category/machine-learning/create-ml/
Thanks to UCI to mantain one of the best ML models repository. The model used in this app could be found at...
https://archive.ics.uci.edu/ml/datasets/Tic-Tac-Toe+Endgame
Dua, D. and Graff, C. (2019). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science.