Papers with Code 아카이브

Deep Reinforcement Learning

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 0
평가표: 0
보존된 평가 기록: 0

코드

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

https://github.com/pku-ai-edge/roadnetsz

MetaVIM: Meta Variationally Intrinsic Motivated Reinforcement Learning for Decentralized Traffic Signal Control

https://github.com/plaffa/discrete-world-models

Deep Neuroevolution of Recurrent and Discrete World Models

https://github.com/pointerformer/pointerformer

Pointerformer: Deep Reinforced Multi-Pointer Transformer for the Traveling Salesman Problem

https://github.com/polixir/NeoRL

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

https://github.com/polixir/neorl2

PID-Inspired Inductive Biases for Deep Reinforcement Learning in Partially Observable Control Tasks

https://github.com/poppinace/libranet

Weighing Counts: Sequential Crowd Counting by Reinforcement Learning

https://github.com/potatoehacker/ArticleDeepNeuroEvolution

Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning

https://github.com/pr-shukla/maddpg-keras

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

https://github.com/prajwalgatti/DRL-Collaboration-and-Competition

Continuous control with deep reinforcement learning

https://github.com/prajwalgatti/DRL-Continuous-Control

Continuous control with deep reinforcement learning

https://github.com/prajwalgatti/DRL-Navigation

Dueling Network Architectures for Deep Reinforcement Learning

https://github.com/pranz24/pytorch-soft-actor-critic

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

https://github.com/proroklab/popgym

Playing Atari with Deep Reinforcement Learning

https://github.com/pschaldenbrand/ContentMaskedLoss

Learning to Paint With Model-based Deep Reinforcement Learning

https://github.com/puppetect/TradingBot-tensorflow

Deep Reinforcement Learning with Double Q-learning

https://github.com/pwc-1/Paper-9/tree/main/4/PCGrad-mindspore-example

Gradient Surgery for Multi-Task Learning

https://github.com/pwc-1/Paper-9/tree/main/4/rand_conv-master

Network Randomization: A Simple Technique for Generalization in Deep Reinforcement Learning

https://github.com/pwc-1/Paper-9/tree/main/7/PCGrad-mindspore-example

Gradient Surgery for Multi-Task Learning

https://github.com/pwc-1/Paper-9/tree/main/7/Simba

SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning

https://github.com/pwc-1/Paper-9/tree/main/7/rand_conv-master

Network Randomization: A Simple Technique for Generalization in Deep Reinforcement Learning

https://github.com/pytorch/rl/tree/main/examples/a2c

Asynchronous Methods for Deep Reinforcement Learning

https://github.com/pytorch/rl/tree/main/examples/dqn

Playing Atari with Deep Reinforcement Learning

https://github.com/pytorch/rl/tree/main/examples/sac

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

https://github.com/qdevpsi3/quantum-arch-search

Quantum Architecture Search via Deep Reinforcement Learning

https://github.com/qi-pang/mdpfuzz

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

https://github.com/qiankun214/DQN-FlappyBird-python3

Playing Atari with Deep Reinforcement Learning

https://github.com/qihongl/demo-advantage-actor-critic

Asynchronous Methods for Deep Reinforcement Learning

https://github.com/qihongl/dlstm-demo

Asynchronous Methods for Deep Reinforcement Learning

https://github.com/qq303067814/DQLearning-Toolbox

A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem

https://github.com/quantumiracle/Popular-RL-Algorithms

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

https://github.com/quanvuong/handful-of-trials-pytorch

Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models

https://github.com/qyuan7/RNN_RL_molecule

Molecular De Novo Design through Deep Reinforcement Learning

https://github.com/qyuan7/RNN_TL_molecule

Molecular De Novo Design through Deep Reinforcement Learning

https://github.com/raccoon831012/StartCraft2-RL

StarCraft II: A New Challenge for Reinforcement Learning

https://github.com/rainandwind1/MADDPG-reconstruct

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

https://github.com/rainandwind1/MERL

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

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