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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/danilonumeroso/MEG

Optimization of Molecules via Deep Reinforcement Learning

https://github.com/dannysdeng/dqn-pytorch

Distributed Prioritized Experience Replay

https://github.com/darkonhub/darkon

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

https://github.com/darkrush/meta_learn

Continuous control with deep reinforcement learning

https://github.com/darshil333/CSE574

Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

https://github.com/darylfung96/differentiable_plasticity

Differentiable plasticity: training plastic neural networks with backpropagation

https://github.com/dasgringuen/assetto_corsa_gym

Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

https://github.com/data-science-in-mechanical-engineering/hci-gibo

Simple random search provides a competitive approach to reinforcement learning

https://github.com/datamllab/rlcard-tutorial

RLCard: A Toolkit for Reinforcement Learning in Card Games

https://github.com/dave-fernandes/ECGClassifier

Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches

https://github.com/david-abel/continuous_state_sa

Learning State Abstractions for Transfer in Continuous Control

https://github.com/davidandym/task-conflict-in-text-to-text-learners

An Empirical Model of Large-Batch Training

https://github.com/daviddcho/supermario

Playing Atari with Deep Reinforcement Learning

https://github.com/davidsonic/robust-grasp

Robust Adversarial Reinforcement Learning

https://github.com/davidsonic/self_brewed_gym

OpenAI Gym

https://github.com/davidtellez/contrastive-predictive-coding

Representation Learning with Contrastive Predictive Coding

https://github.com/davidzhou9/DeepVol

Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations

https://github.com/dbkgroup/prop_gen

Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation

https://github.com/dchetelat/acer

Continuous control with deep reinforcement learning

https://github.com/debajit15kgp/multiagent-envs

Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

https://github.com/decoderkurt/research_project_school_of_ai_2019

Proximal Policy Optimization Algorithms

https://github.com/deconlabs/Binanace-trading-simulation

Proximal Policy Optimization Algorithms

https://github.com/deconlabs/Binanace_trading_simulation

Proximal Policy Optimization Algorithms

https://github.com/deconlabs/TradingZoo-Dynamic-fee-simulation

Proximal Policy Optimization Algorithms

https://github.com/deepcrypto/Reinforcement-learning-in-portfolio-management-

A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem

https://github.com/deepmind/acme

Acme: A Research Framework for Distributed Reinforcement Learning

https://github.com/deepmind/acme/tree/master/acme/agents/jax/dqn

Munchausen Reinforcement Learning

https://github.com/deepmind/alphastar

AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning

https://github.com/deepmind/deepmind-research/tree/master/transporter

Unsupervised Learning of Object Keypoints for Perception and Control

https://github.com/deepmind/enn_acme

Acme: A Research Framework for Distributed Reinforcement Learning

https://github.com/deepmind/haiku

IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures

https://github.com/deepmind/rgb_stacking

Maximum a Posteriori Policy Optimisation

https://github.com/deepmind/rlax

Deep Reinforcement Learning with Double Q-learning

https://github.com/deepmipt/DeepPavlov

Hybrid Code Networks: practical and efficient end-to-end dialog control with supervised and reinforcement learning

https://github.com/deepmipt/diff_beam_search/tree/master/expected_bleu

Differentiable lower bound for expected BLEU score

https://github.com/deepmipt/expected_bleu

Differentiable lower bound for expected BLEU score

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.