https://github.com/shagunsodhani/consistent-dynamics
공식 코드Learning Powerful Policies by Using Consistent Dynamics Model
Papers with Code 아카이브
Reinforcement Learning
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/shagunsodhani/memory-augmented-self-play
공식 코드https://github.com/shakty/optimal-design
공식 코드Optimal design of experiments to identify latent behavioral types
https://github.com/shamanez/VUSFA-Variational-Universal-Successor-Features-Approximator
공식 코드https://github.com/shaneshixiang/rllabplusplus
공식 코드Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic
https://github.com/shanest/function-words-context
공식 코드https://github.com/shanghai-digital-brain-laboratory/db-football
공식 코드An Empirical Study on Google Research Football Multi-agent Scenarios
https://github.com/shanlior/ExplorationConsciousRL
공식 코드https://github.com/shanzhenren/CPL
공식 코드Collaborative Policy Learning for Open Knowledge Graph Reasoning
https://github.com/shaoqian12/ccil
공식 코드Imitating Cost-Constrained Behaviors in Reinforcement Learning
https://github.com/sharadmv/parasol
공식 코드SOLAR: Deep Structured Representations for Model-Based Reinforcement Learning
https://github.com/sharif1093/dextron
공식 코드End-to-end grasping policies for human-in-the-loop robots via deep reinforcement learning
https://github.com/shariqiqbal2810/MAAC
공식 코드Actor-Attention-Critic for Multi-Agent Reinforcement Learning
https://github.com/shariqiqbal2810/Multi-Explore
공식 코드Coordinated Exploration via Intrinsic Rewards for Multi-Agent Reinforcement Learning
https://github.com/shariqiqbal2810/REFIL
공식 코드Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning
https://github.com/sharkwyf/cgdt
공식 코드Critic-Guided Decision Transformer for Offline Reinforcement Learning
https://github.com/sharma1256/cbf-constrained_ppo
공식 코드Sampling-based Safe Reinforcement Learning for Nonlinear Dynamical Systems
https://github.com/sharonlevy/SafeRoute
공식 코드SafeRoute: Learning to Navigate Streets Safely in an Urban Environment
https://github.com/shashacks/symmetric_rl
공식 코드Symmetric Reinforcement Learning Loss for Robust Learning on Diverse Tasks and Model Scales
https://github.com/shashiongithub/Refresh
공식 코드Ranking Sentences for Extractive Summarization with Reinforcement Learning
https://github.com/shawnwun/NNDIAL
공식 코드https://github.com/shayantaherian/Vehicle-Stabilisation-Using-Reinforcement-Learning
공식 코드Self-adaptive Torque Vectoring Controller Using Reinforcement Learning
https://github.com/shayegano/CASL
공식 코드https://github.com/shehryar-malik/icrl
공식 코드https://github.com/shehzaadzd/MINERVA
공식 코드https://github.com/shengchao-y/maaac-driving
공식 코드Agent-Agnostic Centralized Training for Decentralized Multi-Agent Cooperative Driving
https://github.com/shengrenhou/drl-for-energy-systems-optimal-scheduling
공식 코드Performance Comparison of Deep RL Algorithms for Energy Systems Optimal Scheduling
https://github.com/shengrenhou/rl-adn
공식 코드https://github.com/shengzhang37/SAVE
공식 코드Statistical Inference of the Value Function for Reinforcement Learning in Infinite Horizon Settings
https://github.com/shentao-yang/ampl_neurips2022
공식 코드A Unified Framework for Alternating Offline Model Training and Policy Learning
https://github.com/sherilan/cs285-project
공식 코드https://github.com/sherlock1987/SeqReward
공식 코드https://github.com/shiningsunnyday/mcts-chess
공식 코드Alpha-Mini: Minichess Agent with Deep Reinforcement Learning
https://github.com/shiwj16/SSINet
공식 코드Self-Supervised Discovering of Interpretable Features for Reinforcement Learning
https://github.com/shiwj16/raa-drl
공식 코드Regularized Anderson Acceleration for Off-Policy Deep Reinforcement Learning
https://github.com/shoyua/towards-reward-fairness
공식 코드Towards Reward Fairness in RLHF: From a Resource Allocation Perspective
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.