https://github.com/samiamkhan/4641Project
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
Papers with Code 아카이브
General Reinforcement Learning
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 보존된 평가 기록
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/scottemmons/youngs-cql
https://github.com/sea-snell/implicit-language-q-learning
Offline RL for Natural Language Generation with Implicit Language Q Learning
https://github.com/secury/optidice
OptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation
https://github.com/semanticweights/tarok
https://github.com/seohongpark/ogbench
https://github.com/sgkasselau/pyaixi
https://github.com/shyamal-anadkat/offlinerl
https://github.com/simoll/apo
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
https://github.com/skandermoalla/bet-reproduction
https://github.com/sliao-mi-luku/Chatbot-Reformer
https://github.com/sliao-mi-luku/NLP-Chatbot-Reformer-Trax
https://github.com/snu-mllab/edac
Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble
https://github.com/souvikshanku/HexapawnZero
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
https://github.com/sparkmxy/my-offlinerl
https://github.com/spitis/mrl
Counterfactual Data Augmentation using Locally Factored Dynamics
https://github.com/sradicwebster/mbrl-lib
Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models
https://github.com/stanford-iris-lab/batch-exploration
Batch Exploration with Examples for Scalable Robotic Reinforcement Learning
https://github.com/suragnair/alpha-zero-general
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
https://github.com/svikramank/chess-deepRL
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
https://github.com/teddykoker/performer
https://github.com/tensorflow/minigo
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
https://github.com/tensorflow/models/tree/master/official/nlp/modeling
https://github.com/thibaultdouzon/long-range-document-transformer
https://github.com/thomas-schillaci/SimPLe
https://github.com/timmatheis/learning-to-participate
https://github.com/tinkoff-ai/lb-sac
Q-Ensemble for Offline RL: Don't Scale the Ensemble, Scale the Batch Size
https://github.com/typoverflow/OfflineRL-Lib
Decision Transformer: Reinforcement Learning via Sequence Modeling
https://github.com/ulissigroup/uncertainty_benchmarking
Accurate Uncertainties for Deep Learning Using Calibrated Regression
https://github.com/umd-huang-lab/reinforcement-learning-via-spectral-methods
Can Agents Learn by Analogy? An Inferable Model for PAC Reinforcement Learning
https://github.com/vkartik97/habitat-challenge-two-docker
https://github.com/vub-ai-lab/qwr
Q-Value Weighted Regression: Reinforcement Learning with Limited Data
https://github.com/wangml999/chess_zero
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
https://github.com/wcarvalho/jaxneurorl
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
https://github.com/wenzhe-li/romi
Offline Reinforcement Learning with Reverse Model-based Imagination
https://github.com/wongongv/mbpo_fork
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.