Tag: Reinforcement learning [RL]

Play tic-tac-toe against a reinforcement agent

posted on 2020-05-30T11:27:03Z · last modified on 2020-06-10T11:53:21Z

I finally made an unbeatable tic-tac-toe game in javascript using the qtable obtained in in the first reinforcement learning post. Have Fun going for the tie!

Reinforcement learning from the ground up | part 2: deep Q learning on tic-tac-toe.

posted on 2019-12-22T14:53:34Z · last modified on 2020-06-01T11:36:56Z

Previously, we saw that reinforcement learning worked quite well on tic-tac-toe. However, there’s something unsatisfying about working with a Q-table storing all the possible states of the game. It feels like the Agent simply memorizes each state of the game and acts according to some memorized rules obtained by its huge amount of experience (remember that the Agent played 10,000,000 games during training). In this second part of the reinforcement learning series, we’ll swap out the Q table for a neural network.

Reinforcement learning from the ground up | part 1: tic-tac-toe.

posted on 2019-11-29T12:12:07Z · last modified on 2020-06-01T11:36:56Z

As a first example to reinforcement learning, we’ll make our computer learn by itself how to play tic-tac-toe. As one of the most simple 2 player games, tic-tac-toe is ideal to get started with reinforcement learning, while still being more interesting that learning to play a single player game.