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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/anindyasarkarIITH/Reward_Delay_Attack_DRL

공식 코드

Reward Delay Attacks on Deep Reinforcement Learning

https://github.com/anindyasarkariith/psrl_vas

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A Partially Supervised Reinforcement Learning Framework for Visual Active Search

https://github.com/anmolkabra/score-matching-rl

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Exponential Family Model-Based Reinforcement Learning via Score Matching

https://github.com/ann-w/solving_drl_tasks_with_es_and_linear_policy_networks

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Solving Deep Reinforcement Learning Tasks with Evolution Strategies and Linear Policy Networks

https://github.com/anndvision/vsop

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ReLU to the Rescue: Improve Your On-Policy Actor-Critic with Positive Advantages

https://github.com/anndvision/vsop-3d

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Improving Generalization on the ProcGen Benchmark with Simple Architectural Changes and Scale

https://github.com/anon-researcher-repo/ksl

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Learning Temporally-Consistent Representations for Data-Efficient Reinforcement Learning

https://github.com/anonicml2019/icml_2019_state_abstraction

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Learning State Abstractions for Transfer in Continuous Control

https://github.com/anonymous-iclr22/trust-region-in-multi-agent-reinforcement-learning

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Trust Region Policy Optimisation in Multi-Agent Reinforcement Learning

https://github.com/anonymous902109/raccer

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RACCER: Towards Reachable and Certain Counterfactual Explanations for Reinforcement Learning

https://github.com/anonymous902109/reccover

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ReCCoVER: Detecting Causal Confusion for Explainable Reinforcement Learning

https://github.com/anonymous902109/sgrl

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Semifactual Explanations for Reinforcement Learning

https://github.com/anonymousresearcher5642/functionencoderrl

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Zero-Shot Reinforcement Learning via Function Encoders

https://github.com/anqili/mahalo

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MAHALO: Unifying Offline Reinforcement Learning and Imitation Learning from Observations

https://github.com/antspy/quantized_distillation

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Model compression via distillation and quantization

https://github.com/anyasims/edge-of-reach

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The Edge-of-Reach Problem in Offline Model-Based Reinforcement Learning

https://github.com/anyasims/edge-of-reach-ravl

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The Edge-of-Reach Problem in Offline Model-Based Reinforcement Learning

https://github.com/anyleopeace/DURLECA

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Reinforced Epidemic Control: Saving Both Lives and Economy

https://github.com/aoudsung/tri-crlad

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Semi-supervised Anomaly Detection via Adaptive Reinforcement Learning-Enabled Method with Causal Inference for Sensor Signals

https://github.com/apeterswu/RL4NMT

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A Study of Reinforcement Learning for Neural Machine Translation

https://github.com/apexrl/EBIL-torch

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Energy-Based Imitation Learning

https://github.com/apexrl/diff4rlsurvey

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Diffusion Models for Reinforcement Learning: A Survey

https://github.com/apexrl/gcrl-collection

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Goal-Conditioned Reinforcement Learning: Problems and Solutions

https://github.com/apourchot/CEM-RL

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CEM-RL: Combining evolutionary and gradient-based methods for policy search

https://github.com/apple/ml-reed

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Sample-Efficient Preference-based Reinforcement Learning with Dynamics Aware Rewards

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

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Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning

https://github.com/appletea233/temporal-r1

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Reinforcement Learning Tuning for VideoLLMs: Reward Design and Data Efficiency

https://github.com/applied-ai-lab/genesis

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GENESIS: Generative Scene Inference and Sampling with Object-Centric Latent Representations

https://github.com/applied-machine-learning-lab/rmtl

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Multi-Task Recommendations with Reinforcement Learning

https://github.com/aptx395/deep-spiking-q-networks

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Human-Level Control through Directly-Trained Deep Spiking Q-Networks

https://github.com/aqasch/gadget_rl

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Reinforcement learning with learned gadgets to tackle hard quantum problems on real hardware

https://github.com/aqeel13932/APES

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APES: a Python toolbox for simulating reinforcement learning environments

https://github.com/aqeel13932/mn_project

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Emergence of Adaptive Circadian Rhythms in Deep Reinforcement Learning

https://github.com/aqeelanwar/PEDRA

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Autonomous Navigation via Deep Reinforcement Learning for Resource Constraint Edge Nodes using Transfer Learning

https://github.com/araffin/robotics-rl-srl

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S-RL Toolbox: Environments, Datasets and Evaluation Metrics for State Representation Learning

https://github.com/aralab-unr/ReinforcementLearningWithGA

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Deep Reinforcement Learning using Genetic Algorithm for Parameter Optimization

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