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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/ml-research/rational_activations

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Adaptive Rational Activations to Boost Deep Reinforcement Learning

https://github.com/ml-research/rational_rl

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Adaptive Rational Activations to Boost Deep Reinforcement Learning

https://github.com/ml-research/rational_sl

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Adaptive Rational Activations to Boost Deep Reinforcement Learning

https://github.com/mohmdelsayed/streaming-drl

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Streaming Deep Reinforcement Learning Finally Works

https://github.com/monnalo/uav_navigation

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UAV Obstacle Avoidance by Human-in-the-Loop Reinforcement in Arbitrary 3D Environment

https://github.com/montrealrobotics/iv_rl

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Sample Efficient Deep Reinforcement Learning via Uncertainty Estimation

https://github.com/moporgic/tdl2048

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On Reinforcement Learning for the Game of 2048

https://github.com/morningmoni/HiLAP

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Hierarchical Text Classification with Reinforced Label Assignment

https://github.com/mrjun123/DPETS

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Practical Probabilistic Model-based Deep Reinforcement Learning by Integrating Dropout Uncertainty and Trajectory Sampling

https://github.com/mrkulk/hierarchical-deep-RL

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Deep Reinforcement Learning

https://github.com/mtoquebiau/joint-intrinsic-motivation

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Joint Intrinsic Motivation for Coordinated Exploration in Multi-Agent Deep Reinforcement Learning

https://github.com/mudita11/DE-DDQN

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Deep Reinforcement Learning Based Parameter Control in Differential Evolution

https://github.com/mwalton/ToM-hanabi-neurips19

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Theory of Mind for Deep Reinforcement Learning in Hanabi

https://github.com/myrepositories-hub/mutual-distillation-policy-optimization

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Representation Convergence: Mutual Distillation is Secretly a Form of Regularization

https://github.com/nagisazj/cup

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CUP: Critic-Guided Policy Reuse

https://github.com/natashamjaques/neural_chat

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Way Off-Policy Batch Deep Reinforcement Learning of Implicit Human Preferences in Dialog

https://github.com/nathangrinsztajn/DAG-scheduling

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Geometric Deep Reinforcement Learning for Dynamic DAG Scheduling

https://github.com/nathanlct/iig-rl-benchmark

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Reevaluating Policy Gradient Methods for Imperfect-Information Games

https://github.com/nathanrahn/return-landscapes

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Policy Optimization in a Noisy Neighborhood: On Return Landscapes in Continuous Control

https://github.com/navid-naderi/GraphMIX

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Graph Convolutional Value Decomposition in Multi-Agent Reinforcement Learning

https://github.com/navneet-nmk/pytorch-rl

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Empowerment-driven Exploration using Mutual Information Estimation

https://github.com/neasez/marl

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Deep Reinforcement Learning Framework for Thoracic Diseases Classification via Prior Knowledge Guidance

https://github.com/nedzhaken/socsarl-ol

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Online Context Learning for Socially Compliant Navigation

https://github.com/neilus03/drl_comparative_study

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A Comparative Study of Deep Reinforcement Learning Models: DQN vs PPO vs A2C

https://github.com/nesl/eagle_ptz_cameras

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Eagle: End-to-end Deep Reinforcement Learning based Autonomous Control of PTZ Cameras

https://github.com/neuralnetworkverification/artifact-dasc-docking

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Safe and Reliable Training of Learning-Based Aerospace Controllers

https://github.com/neuralnetworkverification/artifact-fmcad24-docking

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Formally Verifying Deep Reinforcement Learning Controllers with Lyapunov Barrier Certificates

https://github.com/neuralsec/camp-robust-rl

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CAMP in the Odyssey: Provably Robust Reinforcement Learning with Certified Radius Maximization

https://github.com/neurasearch/spotify-xrl-skipping-prediction

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Why People Skip Music? On Predicting Music Skips using Deep Reinforcement Learning

https://github.com/nic-barbara/Lipschitz-RL-Atari

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On Robust Reinforcement Learning with Lipschitz-Bounded Policy Networks

https://github.com/nic-barbara/Lipschitz-RL-MJX

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On Robust Reinforcement Learning with Lipschitz-Bounded Policy Networks

https://github.com/nico-bohlinger/one_policy_to_run_them_all

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One Policy to Run Them All: an End-to-end Learning Approach to Multi-Embodiment Locomotion

https://github.com/nico-bohlinger/rl-x

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RL-X: A Deep Reinforcement Learning Library (not only) for RoboCup

https://github.com/nicob15/parametric-pde-control-with-drl-and-differentiable-l0-sparse-polynomial-policies

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Parametric PDE Control with Deep Reinforcement Learning and Differentiable L0-Sparse Polynomial Policies

https://github.com/nicob15/sparsifying-parametric-models-with-l0

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Parametric PDE Control with Deep Reinforcement Learning and Differentiable L0-Sparse Polynomial Policies

https://github.com/nicob15/state_representation_learning_methods

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Unsupervised Representation Learning in Deep Reinforcement Learning: A Review

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