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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://github.com/takuseno/d3rlpy

공식 코드

Q-learning Decision Transformer: Leveraging Dynamic Programming for Conditional Sequence Modelling in Offline RL

https://github.com/takuyahiraoka/efficient-srgc-rl-with-a-high-rr-and-regularization

공식 코드

Efficient Sparse-Reward Goal-Conditioned Reinforcement Learning with a High Replay Ratio and Regularization

https://github.com/talhabozkus/digital-cousins-for-ensemble-q-learning

공식 코드

Leveraging Digital Cousins for Ensemble Q-Learning in Large-Scale Wireless Networks

https://github.com/talhabozkus/icassp-25-appendix

공식 코드

A Multi-Agent Multi-Environment Mixed Q-Learning for Partially Decentralized Wireless Network Optimization

https://github.com/talhabozkus/tsp_23_supplementary_file

공식 코드

Multi-Timescale Ensemble Q-learning for Markov Decision Process Policy Optimization

https://github.com/teawizardry/schrodingers-camera

공식 코드

Schrödinger's Camera: First Steps Towards a Quantum-Based Privacy Preserving Camera

https://github.com/tensorflow/models

공식 코드

Bridging the Gap Between Value and Policy Based Reinforcement Learning

https://github.com/tgangwani/GuidanceRewards

공식 코드

Learning Guidance Rewards with Trajectory-space Smoothing

https://github.com/thu-rllab/CFCQL

공식 코드

Counterfactual Conservative Q Learning for Offline Multi-agent Reinforcement Learning

https://github.com/tianyucodings/diffusion_trusted_q_learning

공식 코드

Diffusion Policies creating a Trust Region for Offline Reinforcement Learning

https://github.com/tobyleelsz/iqmpc

공식 코드

Reward-free World Models for Online Imitation Learning

https://github.com/tseyde/decqn

공식 코드

Solving Continuous Control via Q-learning

https://github.com/tufts-ai-robotics-group/automaton-guided-cl

공식 코드

Automaton-Guided Curriculum Generation for Reinforcement Learning Agents

https://github.com/tuomaso/radial_rl

공식 코드

Robust Deep Reinforcement Learning through Adversarial Loss

https://github.com/tuomaso/radial_rl_v2

공식 코드

Robust Deep Reinforcement Learning through Adversarial Loss

https://github.com/uber-research/deep-neuroevolution

공식 코드

Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking Agents

https://github.com/ucbtns/dai

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Active inference: demystified and compared

https://github.com/ucuapps/modelicagym

공식 코드

ModelicaGym: Applying Reinforcement Learning to Modelica Models

https://github.com/ulieu/rl_patchy

공식 코드

Dynamic control of self-assembly of quasicrystalline structures through reinforcement learning

https://github.com/veda-s4dhak/AQIL

공식 코드

Augmented Q Imitation Learning (AQIL)

https://github.com/victor-wang-902/synthetic-pretrain-rl

공식 코드

Pre-training with Synthetic Data Helps Offline Reinforcement Learning

https://github.com/vincentberaud/Minecraft-Reinforcement-Learning

공식 코드

Deep Recurrent Q-Learning vs Deep Q-Learning on a simple Partially Observable Markov Decision Process with Minecraft

https://github.com/watchernyu/REDQ

공식 코드

Randomized Ensembled Double Q-Learning: Learning Fast Without a Model

https://github.com/weichenli1223/text-based-adventure-games-using-sac

공식 코드

Learning to Play Text-based Adventure Games with Maximum Entropy Reinforcement Learning

https://github.com/wendelinboehmer/dcg

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Deep Coordination Graphs

https://github.com/wenshuaizhao/optimappo

공식 코드

Optimistic Multi-Agent Policy Gradient

https://github.com/wentaoweng/The-Mean-Squared-Error-of-Double-Q-Learning

공식 코드

The Mean-Squared Error of Double Q-Learning

https://github.com/wh1992v/ggp-rl

공식 코드

Assessing the Potential of Classical Q-learning in General Game Playing

https://github.com/wjh720/QPLEX

공식 코드

QPLEX: Duplex Dueling Multi-Agent Q-Learning

https://github.com/wleiiiii/gym-atc-attack-project

공식 코드

Explainable and Safe Reinforcement Learning for Autonomous Air Mobility

https://github.com/wn-upf/Decentralized_Qlearning_Resource_Allocation_in_WNs

공식 코드

Implications of Decentralized Q-learning Resource Allocation in Wireless Networks

https://github.com/wojzaremba/algorithm-learning

공식 코드

Learning Simple Algorithms from Examples

https://github.com/wponghiran/lsm-rl

공식 코드

Reinforcement Learning with Low-Complexity Liquid State Machines

https://github.com/wsqsgithub/timerobustlearning

공식 코드

Synthesis of Temporally-Robust Policies for Signal Temporal Logic Tasks using Reinforcement Learning

https://github.com/xujinming01/td3aq

공식 코드

Mixed-Integer Optimal Control via Reinforcement Learning: A Case Study on Hybrid Electric Vehicle Energy Management

https://github.com/yamoling/lle

공식 코드

Laser Learning Environment: A new environment for coordination-critical multi-agent tasks

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