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Reinforcement Learning (RL)

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Reinforcement Learning (RL) involves training an agent to take actions in an environment to maximize a cumulative reward signal. The agent interacts with the environment and learns by receiving feedback in the form of rewards or punishments for its actions. The goal of reinforcement learning is to find the optimal policy or decision-making strategy that maximizes the long-term reward.

코드

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

https://github.com/BY571/Munchausen-RL

Munchausen Reinforcement Learning

https://github.com/BY571/Normalized-Advantage-Function-NAF-

Continuous Deep Q-Learning with Model-based Acceleration

https://github.com/BY571/SAC_discrete

Soft Actor-Critic for Discrete Action Settings

https://github.com/BY571/Soft-Actor-Critic-and-Extensions

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

https://github.com/BY571/Upside-Down-Reinforcement-Learning

Reinforcement Learning Upside Down: Don't Predict Rewards -- Just Map Them to Actions

https://github.com/Baichenjia/BHER

Hindsight Experience Replay

https://github.com/Baidi96/text2sql

Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning

https://github.com/Bam4d/GVGAI_GYM

Deep Reinforcement Learning for General Video Game AI

https://github.com/Banmahhhh/HIPI-RL

Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement

https://github.com/Bayesian-Razor/papernotes

SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient

https://github.com/BerenMillidge/DeepActiveInference

Deep Active Inference as Variational Policy Gradients

https://github.com/BertilBraun/ChessBot

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

https://github.com/Bhaney44/MIT_DeepTraffic

DeepTraffic: Crowdsourced Hyperparameter Tuning of Deep Reinforcement Learning Systems for Multi-Agent Dense Traffic Navigation

https://github.com/Bibyutatsu/Self_Driving_Car

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

https://github.com/Bigpig4396/PyTorch-Constrained-Policy-Optimization-CPO

Constrained Policy Optimization

https://github.com/Bigpig4396/PyTorch-Soft-Actor-Critic-SAC

Soft Actor-Critic for Discrete Action Settings

https://github.com/Billijk/DeepQuestionAsking

Modeling question asking using neural program generation

https://github.com/Bmillidgework/DeepActiveInference_Code

Deep Active Inference as Variational Policy Gradients

https://github.com/Bonnevie/rebar

Backpropagation through the Void: Optimizing control variates for black-box gradient estimation

https://github.com/Branbados/rlcard

RLCard: A Toolkit for Reinforcement Learning in Card Games

https://github.com/Brandon-Rozek/DeepRL

Prioritized Experience Replay

https://github.com/BroCoLySTyLe/SQLovaReview

SQLNet: Generating Structured Queries From Natural Language Without Reinforcement Learning

https://github.com/Brook1711/RIS_components

Continuous control with deep reinforcement learning

https://github.com/BrutishGuy/ContinuumArmedBandits

A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning

https://github.com/Burntt/FinRL_Crypto

Deep Reinforcement Learning for Cryptocurrency Trading: Practical Approach to Address Backtest Overfitting

https://github.com/ByMic/PETS

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

https://github.com/CAVED123/METAWORLD

Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning

https://github.com/CAVED123/TD-DPPO

Target-driven Visual Navigation in Indoor Scenes using Deep Reinforcement Learning

https://github.com/CAVED123/Tensorforce

LIFT: Reinforcement Learning in Computer Systems by Learning From Demonstrations

https://github.com/CAVED123/tensorforce-

LIFT: Reinforcement Learning in Computer Systems by Learning From Demonstrations

https://github.com/COMP6248-Reproducability-Challenge/Transfer-Learning

Transfer Learning for Related Reinforcement Learning Tasks via Image-to-Image Translation

https://github.com/CSCI4850/S20-team3-project

Prioritized Experience Replay

https://github.com/CX000/sqlnet_inference_py36

Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning

https://github.com/Cadene/pretrained-models.pytorch

Progressive Neural Architecture Search

https://github.com/CankayaUniversity/ceng-407-408-License-Plate-Recognition-Using-Deep-Learning

Playing Atari with Deep Reinforcement Learning

https://github.com/CatherineWong/dancin_seq2seq

Adversarial Learning for Neural Dialogue Generation

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