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태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 3
- 평가표
- 0
- 보존된 평가 기록
- 0
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Ludeme/LudiiAI
https://github.com/MarkTakken/KataGoToroidal
https://github.com/MerceaOtniel/HybridAlpha
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
https://github.com/Miatto-research-group/muzero
Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
https://github.com/Microsoft/nail_agent
https://github.com/MingzhenY/Projects
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
https://github.com/Neo-The1/ThinkingTicTacToe
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
https://github.com/Nkluge-correa/teeny-tiny_castle
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
https://github.com/SHRIVP/muzero
Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
https://github.com/Sidus-smg/ataxx-ai
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
https://github.com/XiangboGaoBarry/TexasHoldemAI
https://github.com/YuriCat/MuZeroJupyterExample
Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
https://github.com/Yuta123456/poker-ai
https://github.com/Zeta36/chess-alpha-zero
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
https://github.com/Zeta36/muzero
Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
https://github.com/ZiyuanMa/reversi
Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
https://github.com/aduerig/burrus
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
https://github.com/alextrudeau/go_exploit
https://github.com/alignmentresearch/katago-custom
https://github.com/alreadydone/Leela_Phoenix
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
https://github.com/amaar-quadri/PerfectInformationGame
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
https://github.com/amaarquadri/PerfectInformationGame
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
https://github.com/amjshl/compute_efficient_alphazero
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
https://github.com/andyljones/boardlaw
https://github.com/cjohnchen/changebale
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
https://github.com/cjohnchen/mirror
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
https://github.com/cjohnchen/sai
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
https://github.com/cogitoergoread/rlcard3
https://github.com/colindbrown/columbia-deep-learning-project
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
https://github.com/cosmobobak/ttt-ml
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
https://github.com/dangeng/DeepChess
DeepChess: End-to-End Deep Neural Network for Automatic Learning in Chess
https://github.com/datamllab/rlcard-tutorial
https://github.com/dazcona/obstacletower
Obstacle Tower: A Generalization Challenge in Vision, Control, and Planning
https://github.com/dmiracle/muzero-starter
Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
https://github.com/fabricerosay/AlphaGPU
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.