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Q-Learning

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The goal of Q-learning is to learn a policy, which tells an agent what action to take under what circumstances.

<span style="color:grey; opacity: 0.6">( Image credit: Playing Atari with Deep Reinforcement Learning )</span>

코드

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

https://bitbucket.org/scee_ietr/malin-multi-armed-bandit-learning-for-iot-networks-with-grc

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Reinforcement Learning for Physical Layer Communications

https://bitbucket.org/thiagomestrado/journalarticle

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Heuristics, Answer Set Programming and Markov Decision Process for Solving a Set of Spatial Puzzles

https://github.com/011235813/hierarchical-marl

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Hierarchical Cooperative Multi-Agent Reinforcement Learning with Skill Discovery

https://github.com/2raq/code

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Regularized Q-learning through Robust Averaging

https://github.com/Aegis1863/MacLight

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MacLight: Multi-scene Aggregation Convolutional Learning for Traffic Signal Control

https://github.com/AlexS28/SABER

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SABER: Data-Driven Motion Planner for Autonomously Navigating Heterogeneous Robots

https://github.com/AmazingAng/VER

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Revisiting Prioritized Experience Replay: A Value Perspective

https://github.com/ChunyuanLI/RAS

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Adversarial Learning of a Sampler Based on an Unnormalized Distribution

https://github.com/CrickWu/Swtich-DDQ

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Switch-based Active Deep Dyna-Q: Efficient Adaptive Planning for Task-Completion Dialogue Policy Learning

https://github.com/Data-Science-in-Mechanical-Engineering/cheq

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Contextualized Hybrid Ensemble Q-learning: Learning Fast with Control Priors

https://github.com/Div99/IQ-Learn

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IQ-Learn: Inverse soft-Q Learning for Imitation

https://github.com/FMZennaro/CTF-RL

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Modeling Penetration Testing with Reinforcement Learning Using Capture-the-Flag Challenges: Trade-offs between Model-free Learning and A Priori Knowledge

https://github.com/FMZennaro/CTF-SQL

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Simulating SQL Injection Vulnerability Exploitation Using Q-Learning Reinforcement Learning Agents

https://github.com/FengdiC/OTTD

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Target Networks and Over-parameterization Stabilize Off-policy Bootstrapping with Function Approximation

https://github.com/FlemmingKondrup/DeepVent

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Towards Safe Mechanical Ventilation Treatment Using Deep Offline Reinforcement Learning

https://github.com/Grottoh/Deep-Active-Inference-for-Partially-Observable-MDPs

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Deep Active Inference for Partially Observable MDPs

https://github.com/HJDQN/HJQ

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Hamilton-Jacobi Deep Q-Learning for Deterministic Continuous-Time Systems with Lipschitz Continuous Controls

https://github.com/HanGuo97/soft-Q-learning-for-text-generation

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Efficient (Soft) Q-Learning for Text Generation with Limited Good Data

https://github.com/Hananel-Hazan/bindsnet

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

https://github.com/HeyuanMingong/iwies

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Instance Weighted Incremental Evolution Strategies for Reinforcement Learning in Dynamic Environments

https://github.com/Holmeswww/ml-uwac

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Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning

https://github.com/IBM/context-relevant-pruning-textrl

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Bootstrapped Q-learning with Context Relevant Observation Pruning to Generalize in Text-based Games

https://github.com/JHL-HUST/VSR-LKH

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Combining Reinforcement Learning with Lin-Kernighan-Helsgaun Algorithm for the Traveling Salesman Problem

https://github.com/JaeyoungLee-UoA/PIs-for-RL-Problems-in-CTS

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Policy Iterations for Reinforcement Learning Problems in Continuous Time and Space -- Fundamental Theory and Methods

https://github.com/Jiang-HB/AC_CDQ

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Action Candidate Based Clipped Double Q-learning for Discrete and Continuous Action Tasks

https://github.com/Karim-53/Reinforcement-Learning-Malaria-Control-KDDCup-2019

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Policy Learning for Malaria Control

https://github.com/Lamperougeyxy/GHQ

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GHQ: Grouped Hybrid Q Learning for Heterogeneous Cooperative Multi-agent Reinforcement Learning

https://github.com/LorenJAnderson/uav-2d-greedyshooter-rl

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On Solving the 2-Dimensional Greedy Shooter Problem for UAVs

https://github.com/ManipulativeConsultant/AutonomousDrivingCookbook

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Adaptive Symmetric Reward Noising for Reinforcement Learning

https://github.com/MarkCodering/Deep-Reinforcement-Learning-using-quDNN

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Deep-Q Learning with Hybrid Quantum Neural Network on Solving Maze Problems

https://github.com/MathPhysSim/FERMI_RL_Paper

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Model-free and Bayesian Ensembling Model-based Deep Reinforcement Learning for Particle Accelerator Control Demonstrated on the FERMI FEL

https://github.com/MatthewChang/video-dqn

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Semantic Visual Navigation by Watching YouTube Videos

https://github.com/MehdiKhamassi/SocialMetaLearning

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Active exploration in parameterized reinforcement learning

https://github.com/Microsoft/StateDecoding

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Provably efficient RL with Rich Observations via Latent State Decoding

https://github.com/Miffyli/rl-human-prior-tricks

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Distilling Reinforcement Learning Tricks for Video Games

https://github.com/MonkieDein/DRA-Q-LA

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Q-learning for Quantile MDPs: A Decomposition, Performance, and Convergence Analysis

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