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Results tagged with q-learning
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user 71449
For questions related to the Q-learning algorithm, which is a model-free and temporal-difference reinforcement learning algorithm that attempts to approximate the Q function, which is a function that, given a state s and an action a, returns a real number that represents the return (or value) of state s when action a is taken from s. Q-learning was introduced in the PhD thesis "Learning from Delayed Rewards" (1989) by Watkins.
2
votes
1
answer
299
views
Q learning (DQN) strategy for a multiplayer zero-sum game
I have been looking for ways to train a Q-learning agent for a multiplayer zero-sum game (a variation of Tic-Tac-Toe in my case). I came up with a learning strategy I haven't found anywhere else, and …
3
votes
1
answer
301
views
Does the DoubleDQN algorithm use a target network or two separate policies?
I've been looking for ways to improve my DQN. That is when I found the Double DQN algorithm. After looking at explanatory videos and posts, I've seen conflicting information:
The Double DQN algorithm …