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Reinforcement Learning (RL)

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하위 태스크: 6
평가표: 2
보존된 평가 기록: 3

Reinforcement Learning (RL) involves training an agent to take actions in an environment to maximize a cumulative reward signal. The agent interacts with the environment and learns by receiving feedback in the form of rewards or punishments for its actions. The goal of reinforcement learning is to find the optimal policy or decision-making strategy that maximizes the long-term reward.

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/Rajesh-Siraskar/Reinforcement-Learning-for-Control-of-Valves

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Reinforcement Learning for Control of Valves

https://github.com/RamnathKumar181/Adversarial-Learning-Dynamics-in-RL

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Boosting Exploration in Multi-Task Reinforcement Learning using Adversarial Networks

https://github.com/RationalityEnhancement/InterpretableStrategyDiscovery

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Automatic Discovery of Interpretable Planning Strategies

https://github.com/RetailMarketingAI/retailsynth-agentsim

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Simulation-Based Benchmarking of Reinforcement Learning Agents for Personalized Retail Promotions

https://github.com/RobertTLange/action-grammars-hrl

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Semantic RL with Action Grammars: Data-Efficient Learning of Hierarchical Task Abstractions

https://github.com/RobustFieldAutonomyLab/DRL_graph_exploration

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Autonomous Exploration Under Uncertainty via Deep Reinforcement Learning on Graphs

https://github.com/RobustStabilityGuaranteeRL/RobustStabilityGuaranteeRL

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$H_\infty$ Model-free Reinforcement Learning with Robust Stability Guarantee

https://github.com/RockySJ/ampo

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Model-based Policy Optimization with Unsupervised Model Adaptation

https://github.com/RodrigoToroIcarte/reward_machines

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Reward Machines: Exploiting Reward Function Structure in Reinforcement Learning

https://github.com/RonanFR/UCRL

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Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning

https://github.com/RunzheStat/D2OPE

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Deeply-Debiased Off-Policy Interval Estimation

https://github.com/RunzheYang/MORL

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A Generalized Algorithm for Multi-Objective Reinforcement Learning and Policy Adaptation

https://github.com/RuohanW/RED

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Random Expert Distillation: Imitation Learning via Expert Policy Support Estimation

https://github.com/SNAS-Series/SNAS-Series

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SNAS: Stochastic Neural Architecture Search

https://github.com/SOPR-T/SOPR-T

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Supervised Off-Policy Ranking

https://github.com/SRI-AIC/InterestingnessXRL

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Interestingness Elements for Explainable Reinforcement Learning: Understanding Agents' Capabilities and Limitations

https://github.com/SVJayanthi/dmcontrol-generalization-benchmark

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Unified State Representation Learning under Data Augmentation

https://github.com/SaeedTafazzol/curious_explorer

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Curious Exploration and Return-based Memory Restoration for Deep Reinforcement Learning

https://github.com/SafeRL-Lab/Safe-Multi-Objective-MuJoCo

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Safe and Balanced: A Framework for Constrained Multi-Objective Reinforcement Learning

https://github.com/SaminYeasar/Off_Policy_Adversarial_Inverse_Reinforcement_Learning

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Off-Policy Adversarial Inverse Reinforcement Learning

https://github.com/SaminYeasar/sparse_reg

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Sparse-Reg: Improving Sample Complexity in Offline Reinforcement Learning using Sparsity

https://github.com/SamuelMallick/dmpcrl-concept

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Multi-Agent Reinforcement Learning via Distributed MPC as a Function Approximator

https://github.com/SarodYatawatta/smart-calibration

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Deep reinforcement learning for smart calibration of radio telescopes

https://github.com/Scitator/Run-Skeleton-Run

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Run, skeleton, run: skeletal model in a physics-based simulation

https://github.com/Scitator/run-skeleton-run-in-3d

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Sample Efficient Ensemble Learning with Catalyst.RL

https://github.com/ScottJordan/EvaluationOfRLAlgs

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Evaluating the Performance of Reinforcement Learning Algorithms

https://github.com/SeldonIO/alibi

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Model-agnostic and Scalable Counterfactual Explanations via Reinforcement Learning

https://github.com/ShangtongZhang/DeepRL

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QUOTA: The Quantile Option Architecture for Reinforcement Learning

https://github.com/ShaniGam/RL-GAN

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Transfer Learning for Related Reinforcement Learning Tasks via Image-to-Image Translation

https://github.com/ShawK91/erl_paper_nips18

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Evolution-Guided Policy Gradient in Reinforcement Learning

https://github.com/Sheng-J/DOM-Q-NET

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DOM-Q-NET: Grounded RL on Structured Language

https://github.com/ShengranHu/Thought-Cloning

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Thought Cloning: Learning to Think while Acting by Imitating Human Thinking

https://github.com/ShengrenHou/Energy-management-MIP-Deep-Reinforcement-Learning

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Optimal Energy System Scheduling Using A Constraint-Aware Reinforcement Learning Algorithm

https://github.com/Shilun-Allan-Li/2048-reinforcement_learning

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Playing 2048 With Reinforcement Learning

https://github.com/Shuijing725/CrowdNav_DSRNN

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Decentralized Structural-RNN for Robot Crowd Navigation with Deep Reinforcement Learning

https://github.com/Shuijing725/VAE_trait_inference

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Learning to Navigate Intersections with Unsupervised Driver Trait Inference

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