Questions tagged [tic-tac-toe]
For questions about the tic-tac-toe (aka noughts and crosses) in the context of artificial intelligence.
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How does the Markov assumption hold true for episodic task?
The Markov assumption assumes that the current state is sufficient for taking the next action.
Consider an episodic task, where the RL agent is trying to learn to play the game of tic-tac-toe. Here, ...
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How are rewards calculated for episodic tasks like playing chess or tic-tac-toe?
I am new to Reinforcement Learning and trying to understand the concept of reaping rewards during episodic tasks. I think in games like tic-tac-toe, rewards will be in terms of a win or lose. But does ...
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What is the optimal score for Tic Tac Toe for a reinforcement learning agent against a random opponent?
I guess this problem is encountered by everyone trying to solve Tic Tac Toe with various flavors of reinforcement learning.
The answer is not "always win" because the random opponent may ...
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Non-Neural Network algorithms for large state space in zero sum games
I was reading online that tic-tac-toe has a state space of $3^9 = 19,683$. From my basic understanding, this sounds too large to use tabular Q-learning, as the Q table would be huge. Is this correct?
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Why isn't my Q-Learning agent able to play tic-tac-toe?
I tried to build a Q-learning agent which you can play tic tac toe against after training.
Unfortunately, the agent performs pretty poorly. He tries to win but does not try to make me 'not winning' ...
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How do we find the length (depth) of the game tic-tac-toe in adversarial search?
When we perform the tic-tac-toe game using adversarial search, I know how to make a tree. Is there a way to find the depth of the tree, and which level is the last level?
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How can both agents know the terminal reward in self-play reinforcement learning?
There seems to be a major difference in 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 ...
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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 ...
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How should I represent the input to a neural network for the games of tic-tac-toe, checkers or chess?
I've been reading a lot about TD-Gammon recently as I'm exploring options for AI in a video game I'm making. The video game is a turn-based positional sort of game, i.e. a "units", or game ...
