Questions tagged [self-play]
For questions about the technique of "self play" in reinforcement learning in relation to combinatorial games and games in general.
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What does self-play in reinforcement learning lead to?
Suppose, instead of playing against a random opponent, the reinforcement learning algorithm described above played against itself, with both sides learning. What do you think would happen in this case?...
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40 views
Generalising performance of Q-learning agent through self-play in a two-player game (MCTS?)
I'm using Q-learning (off-policy TD-control as specified in Sutton's book on pg 131) to train an agent to play connect four. My goal is to create a strong player (superhuman performance?) purely by ...
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0answers
85 views
How to correctly implement self-play with DQN?
I have an environment where an agent faces an equal opponent, and while I've achieved OK performance implementing DQN and treating the opponent as a part of the environment, I think performance would ...
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0answers
43 views
Is it possible to use just one policy in a self-play setting? [closed]
I would like to ask is it possible to train an agent under self-playing setting but with just one policy to be trained? What are the foreseeable problems with such an implementation? My concern is as ...
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45 views
How exactly does self-play work, and how does it relate to MCTS?
I am working towards using RL to create an AI for a two-player, hidden-information, a turn-based board game. I have just finished David Silver's RL course and Denny Britz's coding exercises, and so am ...
3
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1answer
53 views
AlphaZero: updating policy & choosing move
I’ve been doping some research on the principles behind AlphaZero.
Especially this ‘cheat sheet’(1) and this implementation(2) (in Connect4) were very useful.
Yet, I still have two important ...
3
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0answers
39 views
How to deal with nonstationary rewards in asymmetric self-play reinforcement learning?
Suppose we're training two agents to play an asymmetric game from scratch using self play (like Zerg vs. Protoss in Starcraft). During training one of the agents can become stronger (discover a good ...
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1answer
115 views
What will Q-values look like in self-play tic-tac-toe?
This corresponds to Exercise 1.1 of RLBook, and a discussion followed from here.
Considering two reward schemes-
Win = +1, Draw = 0, Loss = -1
Win = +1, Draw or Loss = 0
Can we say something about ...
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1answer
87 views
How can I oppose two AI agents with keras / tensoflow?
I am trying to use tensorflow / keras to play a text based game. The game opposes two players that play by answering questions by choosing an answer among the proposed ones.
Game resembles this:
...
3
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2answers
2k views
Why does self-playing TicTacToe not become perfect?
I trained a DQN that learns TicTacToe by playing against itself with a reward of -1/0/+1 for a loss/draw/win. Every 500 episodes I test the progress by letting it play some episodes (also 500) against ...
2
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2answers
395 views
How to see terminal reward in self-play reinforcement learning?
there seems to be a major difference how the terminal reward is received/handled in self-play RL vs "normal" RL which confuses me.
I implemented TicTacToe the normal way, where a single agent plays ...
3
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1answer
443 views
What are good learning strategies for Deep Q-Network with opponents?
I am trying to find out what are some good learning strategies for Deep Q-Network with opponents. Let's consider the well known game Tic-Tac-Toe as an example:
How should an opponent be implemented ...
