Game of Go
19 papers with code • 1 benchmarks • 1 datasets
Go is an abstract strategy board game for two players, in which the aim is to surround more territory than the opponent. The task is to train an agent to play the game and be superior to other players.
Benchmarks
These leaderboards are used to track progress in Game of Go
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Libraries
Use these libraries to find Game of Go models and implementations
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Latest papers
Monte Carlo Tree Search with Boltzmann Exploration
Monte-Carlo Tree Search (MCTS) methods, such as Upper Confidence Bound applied to Trees (UCT), are instrumental to automated planning techniques.
Active Reinforcement Learning for Robust Building Control
Reinforcement learning (RL) is a powerful tool for optimal control that has found great success in Atari games, the game of Go, robotic control, and building optimization.
Are AlphaZero-like Agents Robust to Adversarial Perturbations?
lan-lc/adversarial_example_of_Go
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Given that the state space of Go is extremely large and a human player can play the game from any legal state, we ask whether adversarial states exist for Go AIs that may lead them to play surprisingly wrong actions.
Planning in Stochastic Environments with a Learned Model
opendilab/LightZero
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ICLR 2022
However, previous instantiations of this approach were limited to the use of deterministic models.
Learning and Planning in Complex Action Spaces
Instead, only small subsets of actions can be sampled for the purpose of policy evaluation and improvement.
Conservative Optimistic Policy Optimization via Multiple Importance Sampling
WolfLo/optimist
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Reinforcement Learning (RL) has been able to solve hard problems such as playing Atari games or solving the game of Go, with a unified approach.
Visualizing MuZero Models
kaesve/muzero
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ICML Workshop URL 2021
In contrast to standard forward dynamics models that predict a full next state, value equivalent models are trained to predict a future value, thereby emphasizing value relevant information in the representations.
Derived metrics for the game of Go -- intrinsic network strength assessment and cheat-detection
This gives an intrinsic strength measurement for the neural network.
The Computational Limits of Deep Learning
Deep learning's recent history has been one of achievement: from triumphing over humans in the game of Go to world-leading performance in image classification, voice recognition, translation, and other tasks.
Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
werner-duvaud/muzero-general
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When evaluated on Go, chess and shogi, without any knowledge of the game rules, MuZero matched the superhuman performance of the AlphaZero algorithm that was supplied with the game rules.
