https://github.com/marwaltz/tud_rl
공식 코드Addressing Maximization Bias in Reinforcement Learning with Two-Sample Testing
Papers with Code 아카이브
Q-Learning
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The goal of Q-learning is to learn a policy, which tells an agent what action to take under what circumstances.
<span style="color:grey; opacity: 0.6">( Image credit: Playing Atari with Deep Reinforcement Learning )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/mcederle99/fairmss
공식 코드https://github.com/meshal-h/ucb-f
공식 코드Sample Efficient Reinforcement Learning with Partial Dynamics Knowledge
https://github.com/metaevo/q-mamba
공식 코드Meta-Black-Box-Optimization through Offline Q-function Learning
https://github.com/metavaluelearning/metavaluelearning
공식 코드Meta-Value Learning: a General Framework for Learning with Learning Awareness
https://github.com/microsoft/Table2Charts
공식 코드Table2Charts: Recommending Charts by Learning Shared Table Representations
https://github.com/microsoft/orchestrated-value-mapping
공식 코드https://github.com/ml-jku/reactive-exploration
공식 코드Reactive Exploration to Cope with Non-Stationarity in Lifelong Reinforcement Learning
https://github.com/mlii/mfrl
공식 코드https://github.com/mohmdelsayed/streaming-drl
공식 코드https://github.com/motokiomura/MXQL
공식 코드https://github.com/mselser95/optimal-market-making
공식 코드https://github.com/mttga/purejaxql
공식 코드https://github.com/mttga/pymarl_transformers
공식 코드https://github.com/mudita11/DE-DDQN
공식 코드Deep Reinforcement Learning Based Parameter Control in Differential Evolution
https://github.com/mwydmuch/ViZDoom
공식 코드ViZDoom: A Doom-based AI Research Platform for Visual Reinforcement Learning
https://github.com/myyura/minimax-dqn
공식 코드M$^2$DQN: A Robust Method for Accelerating Deep Q-learning Network
https://github.com/nakamotoo/cal-ql
공식 코드Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning
https://github.com/natashamjaques/neural_chat
공식 코드Way Off-Policy Batch Deep Reinforcement Learning of Implicit Human Preferences in Dialog
https://github.com/nbatfai/amminadab
공식 코드A disembodied developmental robotic agent called Samu Bátfai
https://github.com/nbatfai/hezron
공식 코드A disembodied developmental robotic agent called Samu Bátfai
https://github.com/nbatfai/isaac
공식 코드A disembodied developmental robotic agent called Samu Bátfai
https://github.com/nbatfai/jacob
공식 코드A disembodied developmental robotic agent called Samu Bátfai
https://github.com/nbatfai/judah
공식 코드A disembodied developmental robotic agent called Samu Bátfai
https://github.com/nbatfai/perez
공식 코드A disembodied developmental robotic agent called Samu Bátfai
https://github.com/nbatfai/ram
공식 코드A disembodied developmental robotic agent called Samu Bátfai
https://github.com/nbatfai/samu
공식 코드A disembodied developmental robotic agent called Samu Bátfai
https://github.com/needleworm/greenhouse_ai
공식 코드Control of nonlinear, complex and black-boxed greenhouse system with reinforcement learning
https://github.com/nicklashansen/dmcontrol-generalization-benchmark
공식 코드Stabilizing Deep Q-Learning with ConvNets and Vision Transformers under Data Augmentation
https://github.com/nikonikolov/rltf
공식 코드Information-Directed Exploration for Deep Reinforcement Learning
https://github.com/nnguyenu/brkgatss
공식 코드https://github.com/nobodymx/sorl-for-auto-bidding
공식 코드https://github.com/ntavanhoeffelen/daif_carracing
공식 코드Deep Active Inference for Pixel-Based Discrete Control: Evaluation on the Car Racing Problem
https://github.com/oezyurty/exrec
공식 코드Personalized Exercise Recommendation with Semantically-Grounded Knowledge Tracing
https://github.com/omardrwch/ucbmq_code
공식 코드UCB Momentum Q-learning: Correcting the bias without forgetting
https://github.com/omron-sinicx/shinrl
공식 코드ShinRL: A Library for Evaluating RL Algorithms from Theoretical and Practical Perspectives
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.