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Deep Reinforcement Learning

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코드

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

https://github.com/matteobiagiola/drl-testing-experiments

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Testing of Deep Reinforcement Learning Agents with Surrogate Models

https://github.com/mattolson93/counterfactual-state-explanations

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Counterfactual State Explanations for Reinforcement Learning Agents via Generative Deep Learning

https://github.com/maxnaeg/zxreinforce

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Optimizing ZX-Diagrams with Deep Reinforcement Learning

https://github.com/mazqtpopx/cranfield-navigation-gym

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Benchmarking Deep Reinforcement Learning for Navigation in Denied Sensor Environments

https://github.com/mbar0075/sarlvision

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Integrating Saliency Ranking and Reinforcement Learning for Enhanced Object Detection

https://github.com/mchancan/citylearn

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CityLearn: Diverse Real-World Environments for Sample-Efficient Navigation Policy Learning

https://github.com/mchldann/SpectralDQN

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Adapting to Reward Progressivity via Spectral Reinforcement Learning

https://github.com/mcogswell/evolang

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Emergence of Compositional Language with Deep Generational Transmission

https://github.com/mees/vapo

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Affordance Learning from Play for Sample-Efficient Policy Learning

https://github.com/mengf1/PAL

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Learning how to Active Learn: A Deep Reinforcement Learning Approach

https://github.com/menggedu/discover

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DISCOVER: Deep identification of symbolically concise open-form PDEs via enhanced reinforcement-learning

https://github.com/mengli11235/swin-dqn

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Deep Reinforcement Learning with Swin Transformers

https://github.com/merlresearch/gram

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GRAM: Generalization in Deep RL with a Robust Adaptation Module

https://github.com/metekemertas/RobustBisimulation

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Towards Robust Bisimulation Metric Learning

https://github.com/mewtwo1996/relax

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ReLAX: Reinforcement Learning Agent eXplainer for Arbitrary Predictive Models

https://github.com/mfe7/cadrl_ros

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Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement Learning

https://github.com/mgbukov/rl_disentangle

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Reinforcement Learning to Disentangle Multiqubit Quantum States from Partial Observations

https://github.com/mgkumar138/TDHL_6PA

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A nonlinear hidden layer enables actor-critic agents to learn multiple paired association navigation

https://github.com/mgoulao/tov-vicreg

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Pretraining the Vision Transformer using self-supervised methods for vision based Deep Reinforcement Learning

https://github.com/mhammoud115/da-rl

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Data Assimilation in Chaotic Systems Using Deep Reinforcement Learning

https://github.com/mhauskn/dqn-hfo

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Deep Reinforcement Learning in Parameterized Action Space

https://github.com/microsoft/Mask-based-Latent-Reconstruction

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Mask-based Latent Reconstruction for Reinforcement Learning

https://github.com/microsoft/Playvirtual

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PlayVirtual: Augmenting Cycle-Consistent Virtual Trajectories for Reinforcement Learning

https://github.com/miguelsvasco/muse

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How to Sense the World: Leveraging Hierarchy in Multimodal Perception for Robust Reinforcement Learning Agents

https://github.com/mila-iqia/SGI

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Pretraining Representations for Data-Efficient Reinforcement Learning

https://github.com/mila-iqia/casande-rl

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Towards Trustworthy Automatic Diagnosis Systems by Emulating Doctors' Reasoning with Deep Reinforcement Learning

https://github.com/mila-iqia/conscious-planning

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A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning

https://github.com/mila-iqia/spr

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Data-Efficient Reinforcement Learning with Self-Predictive Representations

https://github.com/mingyucai/Modular_Deep_RL_E-LDGBA

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Modular Deep Reinforcement Learning for Continuous Motion Planning with Temporal Logic

https://github.com/mit-acl/gym-collision-avoidance

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Collision Avoidance in Pedestrian-Rich Environments with Deep Reinforcement Learning

https://github.com/mit-acl/nn_robustness_analysis

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Neural Network Verification in Control

https://github.com/mit-wu-lab/automatic_vehicular_control

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Unified Automatic Control of Vehicular Systems with Reinforcement Learning

https://github.com/mitkina/EnvironmentPrediction

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Finding Failures in High-Fidelity Simulation using Adaptive Stress Testing and the Backward Algorithm

https://github.com/mitre/arlin

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Utilizing Explainability Techniques for Reinforcement Learning Model Assurance

https://github.com/miyosuda/async_deep_reinforce

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Vision-based deep execution monitoring

https://github.com/mklissa/moc

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Flexible Option Learning

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