How to Train a Deep Learning TensorFlow Analytic to Play Checkers
Bot Libre now allows you to create generic deep learning analytics and train them through our web API. Deep learning analytics can be used for a wide array of purposes to analyze and make predications on data. This example shows how to train a deep learning analytic to play checkers.
You can use either the Bot Libre deep learning library, or the TensorFlow deep learning library. You can choose the inputs, outputs, and layers.
The web API endpoint to train the network is:
The web API endpoint to test the network is:
Create the Analytic
1. Go to the Deep Learning page and create a new analytic.
2. Configure the network with the following settings:
3. Click on "Save", and then "Reset Network".
Train the Analytic
You can use our Java checkers program to train your Checkers analytic.
You can find it here: https://github.com/BotLibre/BotLibre/blob/master/ai-engine/source/org/botlibre/game/Checkers.java.
1. Clone our BotLibre GitHub repository, and open the Checkers.java file in your preferred Java IDE.
2. Edit apiDetails with your API details:
3. Use the learnGames method to train your analytic. We provide several playing strategies to train with in the Strategy class. Some examples have been provided for you to use.
4. You can use the playGames method to test your analytic against several playing strategies.
Create a Checkers Chatbot
Now that you have an analytic trained to play Checkers, you can create your own Checkers chatbot with your own analytic!
Follow this tutorial to create your Checkers chatbot.
Then, modify line 283 of the Checkers Self script with your application ID and analytic ID to connect it to your analytic.
Here is an example Checkers chatbot for you to try: https://www.botlibre.com/browse?id=18546151.
If you encountered any issues, or would like help setting up your bot please email us at [email protected] or upgrade to our Platinum service and we can build your bot for you.