Artificial Intelligence

Questions tagged [self-play]

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For questions about the technique of "self play" in reinforcement learning in relation to combinatorial games and games in general.

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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
57 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
39 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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0answers
39 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 ...
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0answers
26 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 ...
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0answers
36 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
102 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
84 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: ...
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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
344 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 ...
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1answer
399 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 ...