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Reinforcement Learning

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코드

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

https://github.com/Holmeswww/ml-uwac

공식 코드

Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning

https://github.com/Hong-Lab-UMN-ECE/IRLAlignment

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From Demonstrations to Rewards: Alignment Without Explicit Human Preferences

https://github.com/Hongshen-Yang/pair-trading-envs

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Reinforcement Learning Pair Trading: A Dynamic Scaling approach

https://github.com/HumanCompatibleAI/adversarial-policies

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Adversarial Policies: Attacking Deep Reinforcement Learning

https://github.com/HumanCompatibleAI/atari-irl

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Inverse reinforcement learning for video games

https://github.com/HumanCompatibleAI/imitation

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imitation: Clean Imitation Learning Implementations

https://github.com/HumanCompatibleAI/population-irl

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Multi-task Maximum Entropy Inverse Reinforcement Learning

https://github.com/HumanCompatibleAI/rlsp

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Preferences Implicit in the State of the World

https://github.com/HxLyn3/MPPVE

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Model-based Reinforcement Learning with Multi-step Plan Value Estimation

https://github.com/IBM/FormalML

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CertRL: Formalizing Convergence Proofs for Value and Policy Iteration in Coq

https://github.com/IBM/TRAIL

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A Deep Reinforcement Learning Approach to First-Order Logic Theorem Proving

https://github.com/IBM/constrained-rl

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Constrained Exploration and Recovery from Experience Shaping

https://github.com/IBM/online-alt-min

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Beyond Backprop: Online Alternating Minimization with Auxiliary Variables

https://github.com/IBM/parl_agents

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Hierarchical Reinforcement Learning with AI Planning Models

https://github.com/IBM/permuted-bAbI-dialog-tasks

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Learning End-to-End Goal-Oriented Dialog with Multiple Answers

https://github.com/IBM/regen

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ReGen: Reinforcement Learning for Text and Knowledge Base Generation using Pretrained Language Models

https://github.com/IDSIA/marl

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Hierarchical Multi-Agent Reinforcement Learning for Air Combat Maneuvering

https://github.com/IGITUGraz/spore-nest-module

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Embodied Synaptic Plasticity with Online Reinforcement learning

https://github.com/ImanRHT/QECO

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QECO: A QoE-Oriented Computation Offloading Algorithm based on Deep Reinforcement Learning for Mobile Edge Computing

https://github.com/ImperialNLP/pysimt

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Exploiting Multimodal Reinforcement Learning for Simultaneous Machine Translation

https://github.com/Improbable-AI/dw-offline-rl

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Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced Datasets

https://github.com/IndustAI/risk-and-uncertainty

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Estimating Risk and Uncertainty in Deep Reinforcement Learning

https://github.com/IndustAI/visual-domain-randomization

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Robust Visual Domain Randomization for Reinforcement Learning

https://github.com/InsaneMonster/pasqualini2019prngrl

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Pseudo Random Number Generation: a Reinforcement Learning approach

https://github.com/InsaneMonster/telerl2021

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Deep Reinforcement Learning for URLLC data management on top of scheduled eMBB traffic

https://github.com/IntelLabs/DNS

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DNS: Determinantal Point Process Based Neural Network Sampler for Ensemble Reinforcement Learning

https://github.com/Intelligent-Systems-Research-Group/RL4MicrostructureEvolution

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Deep Reinforcement Learning Methods for Structure-Guided Processing Path Optimization

https://github.com/IoannisKansizoglou/Deep-Feature-Space

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Deep Feature Space: A Geometrical Perspective

https://github.com/IouJenLiu/HTS-RL

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High-Throughput Synchronous Deep RL

https://github.com/IouJenLiu/PIC

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PIC: Permutation Invariant Critic for Multi-Agent Deep Reinforcement Learning

https://github.com/IrisLi17/self-imitation-via-reduction

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Solving Compositional Reinforcement Learning Problems via Task Reduction

https://github.com/IrohXu/Gomoku-XYH19

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UCT-ADP Progressive Bias Algorithm for Solving Gomoku

https://github.com/IsmaelTito/SEC

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Sequential memory improves sample and memory efficiency in Episodic Control

https://github.com/JBLanier/pipeline-psro

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Pipeline PSRO: A Scalable Approach for Finding Approximate Nash Equilibria in Large Games

https://github.com/JHL-HUST/VSR-LKH

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Combining Reinforcement Learning with Lin-Kernighan-Helsgaun Algorithm for the Traveling Salesman Problem

https://github.com/JHU-APL-ISC-Deep-RL/risk-sensitive

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A Risk-Sensitive Approach to Policy Optimization

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