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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/HardikJ7321/AugmentedRandomSearch-AI-

Simple random search provides a competitive approach to reinforcement learning

https://github.com/HarshitaSahai/conversational-agent

Collaborative Multi-Agent Dialogue Model Training Via Reinforcement Learning

https://github.com/HassamSheikh/VIP_Protection_Envs

Universal Policies to Learn Them All

https://github.com/Henreich/ML-Breakout-Pong

Unity: A General Platform for Intelligent Agents

https://github.com/Henreich/ML-Pong

Unity: A General Platform for Intelligent Agents

https://github.com/Henreich/ML-testing

Unity: A General Platform for Intelligent Agents

https://github.com/Henry1iu/ierg5350_rl_course_project

Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks

https://github.com/HeungChangLee/AutoML

DARTS: Differentiable Architecture Search

https://github.com/HilbertXu/MAML-Tensorflow

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/Hitoshi-Nakanishi/MolG

MolGAN: An implicit generative model for small molecular graphs

https://github.com/Hmkhalla/NLP-summarizer

A Deep Reinforced Model for Abstractive Summarization

https://github.com/HoganZhang/pytorch-vsumm-reinforce

Deep Reinforcement Learning for Unsupervised Video Summarization with Diversity-Representativeness Reward

https://github.com/HoldenB/TD3-BC-from-scratch

A Minimalist Approach to Offline Reinforcement Learning

https://github.com/Howuhh/prioritized_experience_replay

Prioritized Experience Replay

https://github.com/HumanCompatibleAI/airl

imitation: Clean Imitation Learning Implementations

https://github.com/HumanCompatibleAI/deep-rlsp

Generative Adversarial Imitation Learning

https://github.com/HumanCompatibleAI/multi-agent

A multi-agent reinforcement learning model of common-pool resource appropriation

https://github.com/HussonnoisMaxence/RL_Algorithms

Deep Reinforcement Learning with Double Q-learning

https://github.com/Hydragon516/Grad-CAM-pytorch

Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization

https://github.com/HzcIrving/DLRL-PlayGround

Distributed Distributional Deterministic Policy Gradients

https://github.com/HzcIrving/DLRL-PlayGround/tree/main/Offline%20RL/AWAC

AWAC: Accelerating Online Reinforcement Learning with Offline Datasets

https://github.com/HzcIrving/DLRL-PlayGround/tree/main/Offline%20RL/BCQ

Off-Policy Deep Reinforcement Learning without Exploration

https://github.com/HzcIrving/DecisionTransformer_StepbyStep

Decision Transformer: Reinforcement Learning via Sequence Modeling

https://github.com/IAARhub/TrucoAnalytics

Deep Reinforcement Learning from Self-Play in Imperfect-Information Games

https://github.com/IBM/automation-of-image-data-preprocessing

Automated Image Data Preprocessing with Deep Reinforcement Learning

https://github.com/IBM/vsrl-framework

Verifiably Safe Off-Model Reinforcement Learning

https://github.com/IGITUGraz/LSNN-official

Long short-term memory and learning-to-learn in networks of spiking neurons

https://github.com/IMAC-projects/mesh-deformation

Modeling 3D Shapes by Reinforcement Learning

https://github.com/INF554MachineLearning/GameAI

An Introduction to Deep Reinforcement Learning

https://github.com/INK-USC/CPL

Collaborative Policy Learning for Open Knowledge Graph Reasoning

https://github.com/IRLL/Atari-Data-Scraper

The Atari Data Scraper

https://github.com/IS2AI/Chest-X-ray-module

Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization

https://github.com/IlyaDobrynin/GridMixup

GridMask Data Augmentation

https://github.com/IlyaGusev/summarus

Deep Reinforcement Learning For Sequence to Sequence Models

https://github.com/Improbable-AI/curiosity_baselines

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch

https://github.com/InSpaceAI/RL-Zoo

Playing Atari with Deep Reinforcement Learning

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