SOTAVerified

Game of Go

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.

Papers

Showing 125 of 62 papers

TitleStatusHype
Mastering Atari, Go, Chess and Shogi by Planning with a Learned ModelCode2
Accelerating Self-Play Learning in GoCode2
Active Reinforcement Learning for Robust Building ControlCode1
Are AlphaZero-like Agents Robust to Adversarial Perturbations?Code1
Planning in Stochastic Environments with a Learned ModelCode1
Visualizing MuZero ModelsCode1
MoËT: Mixture of Expert Trees and its Application to Verifiable Reinforcement LearningCode1
Hyper-Parameter Sweep on AlphaZero GeneralCode1
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning AlgorithmCode1
Move Evaluation in Go Using Deep Convolutional Neural NetworksCode1
Teaching Deep Convolutional Neural Networks to Play GoCode1
Reinforcement Learning in Strategy-Based and Atari Games: A Review of Google DeepMinds Innovations0
MASTER: A Multi-Agent System with LLM Specialized MCTS0
Perceptual Similarity for Measuring Decision-Making Style and Policy Diversity in GamesCode0
Deep Reinforcement Learning for 5*5 Multiplayer Go0
Monte Carlo Tree Search with Boltzmann ExplorationCode0
Task Success is not Enough: Investigating the Use of Video-Language Models as Behavior Critics for Catching Undesirable Agent Behaviors0
Explaining How a Neural Network Play the Go Game and Let People Learn0
Vision Transformers for Computer Go0
AlphaZero Gomoku0
The ProfessionAl Go annotation datasEt (PAGE)0
The cost of passing -- using deep learning AIs to expand our understanding of the ancient game of Go0
Score vs. Winrate in Score-Based Games: which Reward for Reinforcement Learning?0
Spatial State-Action Features for General Games0
Probabilistic DAG Search0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AlphaGo ZeroELO Rating5,185Unverified