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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/pavitrakumar78/Playing-custom-games-using-Deep-Learning

Playing Atari with Deep Reinforcement Learning

https://github.com/pcchenxi/lapo-offlienrl

Latent-Variable Advantage-Weighted Policy Optimization for Offline RL

https://github.com/pearl-utexas/sope

Empirical Study of Off-Policy Policy Evaluation for Reinforcement Learning

https://github.com/pedrodbs/InterestingnessXRL

Interestingness Elements for Explainable Reinforcement Learning: Understanding Agents' Capabilities and Limitations

https://github.com/peisuke/awr

Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning

https://github.com/pemami4911/neural-combinatorial-rl-pytorch

Neural Combinatorial Optimization with Reinforcement Learning

https://github.com/pengyuan-zhou/Multi-agent-RL-traffic-light-control

Flow: A Modular Learning Framework for Mixed Autonomy Traffic

https://github.com/penn-pal-lab/peg

Skew-Fit: State-Covering Self-Supervised Reinforcement Learning

https://github.com/pereirarodrigo/project_spike

Improved robustness of reinforcement learning policies upon conversion to spiking neuronal network platforms applied to ATARI games

https://github.com/pereirarodrigo/spike

Improved robustness of reinforcement learning policies upon conversion to spiking neuronal network platforms applied to ATARI games

https://github.com/perrin-isir/afu

Offline Reinforcement Learning with Implicit Q-Learning

https://github.com/pervasive-ai-lab/crlmaze

Continual Reinforcement Learning in 3D Non-stationary Environments

https://github.com/pervasive-ai-lab/nle-language-wrapper

Sample Factory: Egocentric 3D Control from Pixels at 100000 FPS with Asynchronous Reinforcement Learning

https://github.com/peterhj/arm-pytorch

Regret Minimization for Partially Observable Deep Reinforcement Learning

https://github.com/petsol/ContinuousControl_UnityAgent_DDPG_Udacity

Continuous control with deep reinforcement learning

https://github.com/petsol/MultiAgentCooperation_UnityAgent_MADDPG_Udacity

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

https://github.com/petuum/adaptdl

An Empirical Model of Large-Batch Training

https://github.com/pfnet-research/chainer-differentiable-mpc

Differentiable MPC for End-to-end Planning and Control

https://github.com/phanav/upsaclay-hygieia

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

https://github.com/phigley/taxi

Schema Networks: Zero-shot Transfer with a Generative Causal Model of Intuitive Physics

https://github.com/philtabor/Deep-Q-Learning-Paper-To-Code

Deep Reinforcement Learning with Double Q-learning

https://github.com/philtabor/Multi-Agent-Deep-Deterministic-Policy-Gradients

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

https://github.com/phixion/phixion

Reinforcement Learning: An Overview

https://github.com/phogbinh/handwritten-digit-recognition

Searching for Activation Functions

https://github.com/piEsposito/blitz-bayesian-deep-learning

Weight Uncertainty in Neural Networks

https://github.com/pigfarm/LQAC_code

Exact Asymptotics for Linear Quadratic Adaptive Control

https://github.com/pihey1995/DistributionalRL

A Distributional Perspective on Reinforcement Learning

https://github.com/pipilurj/BONAS

DARTS: Differentiable Architecture Search

https://github.com/piroLight/unity-ml-agent

Unity: A General Platform for Intelligent Agents

https://github.com/pjhool/TF-A2RL-Test

A2-RL: Aesthetics Aware Reinforcement Learning for Image Cropping

https://github.com/pkasala/ContinuesControl

Addressing Function Approximation Error in Actor-Critic Methods

https://github.com/pku-rl/dgn

Graph Convolutional Reinforcement Learning

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

Deep Neuroevolution of Recurrent and Discrete World Models

https://github.com/pliang279/MFN

Multimodal Sentiment Analysis with Word-Level Fusion and Reinforcement Learning

https://github.com/plkmo/AlphaZero_Connect4

Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm

https://github.com/pocokhc/agent57

Agent57: Outperforming the Atari Human Benchmark

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