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Enjoy Reinforcement Learning in Tic-Tac-Toe (2)

ishikari
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3MBTamaño
Android Version Icon2.1+
Versión Android
1.0(30-07-2020)Última versión
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Descripción de Enjoy Reinforcement Learning in Tic-Tac-Toe (2)

The purpose of this app is to familiarize you with Reinforcement Learning (a type of artificial intelligence). This was created using MIT App Inventor. In particular, it takes advantage of the recently released Generic Event blocks.


As an example, we use Tic-Tac-Toe, a well-known and easy game. The main feature of this app is that you can adjust the strength of your opponent computer player according to the degree of reinforcement learning and enjoy the match.


The computer player learns the situation when it loses in the match, so it will become gradually stronger as the match is played many times. Please refer to the following document for details of usage.


https://sparse-dense.blogspot.com/2019/05/enjoy-reinforcement-learning-in-tic-tac.html


Enjoy Reinforcement Learning in Tic-Tac-Toe (2) - Versión 1.0

(30-07-2020)
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NovedadesPlease refer to the following document for details of usage:https://sparse-dense.blogspot.com/2019/05/enjoy-reinforcement-learning-in-tic-tac.html

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Enjoy Reinforcement Learning in Tic-Tac-Toe (2) - Información de APK

Version de la app: 1.0Paquete: appinventor.ai_Fujio_YAMAMOTO.aeTTT_psv1b
Compatibilidad con Android: 2.1+ (Eclair)
Desarrollador:ishikariPermisos:5
Nombre: Enjoy Reinforcement Learning in Tic-Tac-Toe (2)Tamaño: 3 MBDescargas: 0Versión : 1.0Fecha de lanzamiento: 2023-03-31 02:39:16Pantalla mín: SMALLCPU soportada:
ID del paquete: appinventor.ai_Fujio_YAMAMOTO.aeTTT_psv1bFirma SHA1: 97:D6:AE:14:B6:3A:70:66:A6:D0:18:CE:1C:8B:DF:D8:A4:52:BE:6DDesarrollador (CN): AndroidOrganización (O): Google Inc.Localización (L): Mountain ViewPaís (C): USEstado/ciudad (ST): CaliforniaID del paquete: appinventor.ai_Fujio_YAMAMOTO.aeTTT_psv1bFirma SHA1: 97:D6:AE:14:B6:3A:70:66:A6:D0:18:CE:1C:8B:DF:D8:A4:52:BE:6DDesarrollador (CN): AndroidOrganización (O): Google Inc.Localización (L): Mountain ViewPaís (C): USEstado/ciudad (ST): California

Última versión de Enjoy Reinforcement Learning in Tic-Tac-Toe (2)

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30/7/2020
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