https://github.com/danecor/VaST
공식 코드Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation
Papers with Code 아카이브
Deep Reinforcement Learning
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 0
- 보존된 평가 기록
- 0
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/danijar/daydreamer
공식 코드https://github.com/daochenzha/Meta-AAD
공식 코드Meta-AAD: Active Anomaly Detection with Deep Reinforcement Learning
https://github.com/daochenzha/SSRL
공식 코드Simplifying Deep Reinforcement Learning via Self-Supervision
https://github.com/daochenzha/autoshard
공식 코드AutoShard: Automated Embedding Table Sharding for Recommender Systems
https://github.com/daqingliu/CAVP
공식 코드Context-Aware Visual Policy Network for Sequence-Level Image Captioning
https://github.com/darkefyre/sepsisrl
공식 코드https://github.com/data-science-in-mechanical-engineering/polishing-cheq
공식 코드CHEQ-ing the Box: Safe Variable Impedance Learning for Robotic Polishing
https://github.com/davidcotton/gym-d2d
공식 코드GymD2D: A Device-to-Device Underlay Cellular Offload Evaluation Platform
https://github.com/dawoz/jsp-deeprl-seq2seq
공식 코드Job Shop Scheduling via Deep Reinforcement Learning: a Sequence to Sequence approach
https://github.com/dbaranchuk/nns-meets-deep-rl
공식 코드Towards Similarity Graphs Constructed by Deep Reinforcement Learning
https://github.com/dcgym/iroko
공식 코드Iroko: A Framework to Prototype Reinforcement Learning for Data Center Traffic Control
https://github.com/ddaedalus/smpe
공식 코드https://github.com/ddm-lab/greedy-hysteretic-lenient-maibl
공식 코드Learning in Cooperative Multiagent Systems Using Cognitive and Machine Models
https://github.com/ddv-lab/Verifiably_Robust_CP
공식 코드https://github.com/deepmind/ai-safety-gridworlds
공식 코드https://github.com/deepmind/deepmind-research
공식 코드The Difficulty of Passive Learning in Deep Reinforcement Learning
https://github.com/deepmind/deepmind-research/tree/master/physics_planning_games
공식 코드Physically Embedded Planning Problems: New Challenges for Reinforcement Learning
https://github.com/deepmind/diplomacy
공식 코드Learning to Play No-Press Diplomacy with Best Response Policy Iteration
https://github.com/deepmind/dm_memorytasks
공식 코드Generalization of Reinforcement Learners with Working and Episodic Memory
https://github.com/deepmind/lab
공식 코드https://github.com/deepmind/lab2d
공식 코드https://github.com/deepmind/open_spiel
공식 코드A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning
https://github.com/deepmind/pysc2
공식 코드https://github.com/deepmind/spriteworld
공식 코드https://github.com/deepmind/streetlearn
공식 코드https://github.com/deepsense-ai/Distributed-BA3C
공식 코드Distributed Deep Reinforcement Learning: Learn how to play Atari games in 21 minutes
https://github.com/deepwlearning/deepwnetworks
공식 코드Deep W-Networks: Solving Multi-Objective Optimisation Problems With Deep Reinforcement Learning
https://github.com/demon0312/hcvrp_drl
공식 코드Deep Reinforcement Learning for Solving the Heterogeneous Capacitated Vehicle Routing Problem
https://github.com/denisyarats/drq
공식 코드Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels
https://github.com/dennishoftijzer/l-b_augmentation
공식 코드Language-Based Augmentation to Address Shortcut Learning in Object Goal Navigation
https://github.com/dfki-ric-quantum/qdrl-turtlebot-env
공식 코드Quantum Deep Reinforcement Learning for Robot Navigation Tasks
https://github.com/dfki-ric-quantum/qdrl-turtlebot-eval
공식 코드Quantum Deep Reinforcement Learning for Robot Navigation Tasks
https://github.com/dhruvms/DenseTrafficEval
공식 코드Driving in Dense Traffic with Model-Free Reinforcement Learning
https://github.com/dhruvms/HighwayTraffic
공식 코드Driving in Dense Traffic with Model-Free Reinforcement Learning
https://github.com/diambra/arena
공식 코드DIAMBRA Arena: a New Reinforcement Learning Platform for Research and Experimentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.