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Reinforcement Learning

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보존된 평가 기록

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코드

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

https://github.com/GAMES-UChile/mogptk

SAMBA: Safe Model-Based & Active Reinforcement Learning

https://github.com/GMC-DRL/ConfigX

ConfigX: Modular Configuration for Evolutionary Algorithms via Multitask Reinforcement Learning

https://github.com/GT-RIPL/robo-vln

DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion Frames

https://github.com/GaoFangshu/ELF-example

ELF: An Extensive, Lightweight and Flexible Research Platform for Real-time Strategy Games

https://github.com/Gary-Shi/Tank

Playing Atari with Deep Reinforcement Learning

https://github.com/GauravPatel89/Car-Navigation-Simulation-using-TD3

Addressing Function Approximation Error in Actor-Critic Methods

https://github.com/GauthierDmn/question_generation

Machine Comprehension by Text-to-Text Neural Question Generation

https://github.com/GeneralCoder365/agreemate

Decoupling Strategy and Generation in Negotiation Dialogues

https://github.com/GeorgeDUT/MetaRLSAS

RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning

https://github.com/GiadaSimionato/Reasoning_Agents_2020

Proximal Policy Optimization Algorithms

https://github.com/Giovanni3A/LearningDynamics

Neural Replicator Dynamics

https://github.com/GiuliaLanzillotta/INAS

Neural Architecture Search with Reinforcement Learning

https://github.com/Godofnothing/EfficientObjectDetection

Efficient Object Detection in Large Images using Deep Reinforcement Learning

https://github.com/GoingMyWay/dopamine_reward_decomposition

Prioritized Experience Replay

https://github.com/GoodAI/GTN

Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data

https://github.com/Gouet/Acrobot-PPO

Proximal Policy Optimization Algorithms

https://github.com/Gouet/Breakout-V0

Proximal Policy Optimization Algorithms

https://github.com/Gouet/DDPG_PendulumV1

Continuous control with deep reinforcement learning

https://github.com/Gouet/PPO-gym

Proximal Policy Optimization Algorithms

https://github.com/Gouet/PPO-pytorch

Proximal Policy Optimization Algorithms

https://github.com/Gourhari/README

NeVAE: A Deep Generative Model for Molecular Graphs

https://github.com/Gregory-Eales/proximal-policy-optimization

Proximal Policy Optimization Algorithms

https://github.com/GuanSuns/Simple-Human-in-the-Loop-ML-Interface

Widening the Pipeline in Human-Guided Reinforcement Learning with Explanation and Context-Aware Data Augmentation

https://github.com/Guang000/Awesome-Dataset-Distillation

Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data

https://github.com/GuangpingYuan/PNN_Pong_A3C

Progressive Neural Networks

https://github.com/GuessWhatGame/guesswhat

End-to-end optimization of goal-driven and visually grounded dialogue systems

https://github.com/Guillaume-Cr/lunar_lander_per

Prioritized Experience Replay

https://github.com/GuillaumeDufau/Unsupervised_exploration

Planning to Explore via Self-Supervised World Models

https://github.com/Guillemdb/FractalAI

Fractal AI: A fragile theory of intelligence

https://github.com/Guillemdb/fragile

Fractal AI: A fragile theory of intelligence

https://github.com/GuyTevet/SeqGAN-eval

SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient

https://github.com/HAHA-DL/MLDG

Learning to Generalize: Meta-Learning for Domain Generalization

https://github.com/HJDQN/HJQ

Continuous control with deep reinforcement learning

https://github.com/HKUST-KnowComp/MnemonicReader

Reinforced Mnemonic Reader for Machine Reading Comprehension

https://github.com/Haichao-Zhang/IRL

A Connection between Generative Adversarial Networks, Inverse Reinforcement Learning, and Energy-Based Models

https://github.com/Hanjun-Dai/graph_adversarial_attack

Adversarial Attack on Graph Structured Data

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