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Reinforcement Learning

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

https://github.com/mariuslindegaard/curiosity_baselines

공식 코드

Intrinsic Rewards from Self-Organizing Feature Maps for Exploration in Reinforcement Learning

https://github.com/marko-ruman/RL-Correspondence-Learner

공식 코드

Knowledge Transfer in Deep Reinforcement Learning via an RL-Specific GAN-Based Correspondence Function

https://github.com/marko-vasic/moet

공식 코드

MoËT: Mixture of Expert Trees and its Application to Verifiable Reinforcement Learning

https://github.com/markpwoodward/active_osl

공식 코드

Active One-shot Learning

https://github.com/marlbenchmark/on-policy

공식 코드

The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Games

https://github.com/marmotatzju/drl-based-trajectory-tracking

공식 코드

DRL-Based Trajectory Tracking for Motion-Related Modules in Autonomous Driving

https://github.com/marmotlab/SIGMA

공식 코드

SIGMA: Sheaf-Informed Geometric Multi-Agent Pathfinding

https://github.com/martin592/hybrid_AuGMEnT

공식 코드

Multi-timescale memory dynamics in a reinforcement learning network with attention-gated memory

https://github.com/martinballa/pytag

공식 코드

PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games

https://github.com/martinballa/sf-tr

공식 코드

Task Relabelling for Multi-task Transfer using Successor Features

https://github.com/martius-lab/SMORL

공식 코드

Self-supervised Visual Reinforcement Learning with Object-centric Representations

https://github.com/martius-lab/cid-in-rl

공식 코드

Causal Influence Detection for Improving Efficiency in Reinforcement Learning

https://github.com/martius-lab/hits

공식 코드

Hierarchical Reinforcement Learning with Timed Subgoals

https://github.com/marvinalles/c-lap

공식 코드

Constrained Latent Action Policies for Model-Based Offline Reinforcement Learning

https://github.com/marwaltz/tud_rl

공식 코드

Spatial-temporal recurrent reinforcement learning for autonomous ships

https://github.com/mary-wu/smdp

공식 코드

Semi-Markov Offline Reinforcement Learning for Healthcare

https://github.com/maryam-abdool/swim-control

공식 코드

Swim: A General-Purpose, High-Performing, and Efficient Activation Function for Locomotion Control Tasks

https://github.com/masa2203/battery_arbitrage_with_drl

공식 코드

Enhancing Battery Storage Energy Arbitrage with Deep Reinforcement Learning and Time-Series Forecasting

https://github.com/masud99r/bae

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Bootstrap Advantage Estimation for Policy Optimization in Reinforcement Learning

https://github.com/masud99r/thinker

공식 코드

Bootstrap State Representation using Style Transfer for Better Generalization in Deep Reinforcement Learning

https://github.com/matibilkis/marek

공식 코드

Real-time calibration of coherent-state receivers: learning by trial and error

https://github.com/matrl-project/matrl

공식 코드

A Game-Theoretic Approach to Multi-Agent Trust Region Optimization

https://github.com/matsuolab/BREMEN

공식 코드

Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization

https://github.com/matt00n/policygradientsjax

공식 코드

The Definitive Guide to Policy Gradients in Deep Reinforcement Learning: Theory, Algorithms and Implementations

https://github.com/matteobiagiola/drl-testing-experiments

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Testing of Deep Reinforcement Learning Agents with Surrogate Models

https://github.com/matthias-weissenbacher/Quadratic_MLPs_in_RL

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A Quadratic Actor Network for Model-Free Reinforcement Learning

https://github.com/matthias-weissenbacher/SiT

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SiT: Symmetry-Invariant Transformers for Generalisation in Reinforcement Learning

https://github.com/matthieu637/DFRL

공식 코드

Learning Fair Policies in Decentralized Cooperative Multi-Agent Reinforcement Learning

https://github.com/mattolson93/counterfactual-state-explanations

공식 코드

Counterfactual State Explanations for Reinforcement Learning Agents via Generative Deep Learning

https://github.com/mattriemer/mer

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Learning to Learn without Forgetting by Maximizing Transfer and Minimizing Interference

https://github.com/mawbray/Lutein-Dataset

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Safe Chance Constrained Reinforcement Learning for Batch Process Control

https://github.com/maximecb/gym-minigrid

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The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget

https://github.com/maximecb/gym-miniworld

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Addressing Sample Complexity in Visual Tasks Using HER and Hallucinatory GANs

https://github.com/maximilianigl/DVRL

공식 코드

Deep Variational Reinforcement Learning for POMDPs

https://github.com/maximilienlc/nra

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Neuroevolution of Recurrent Architectures on Control Tasks

https://github.com/maxnaeg/zxreinforce

공식 코드

Optimizing ZX-Diagrams with Deep Reinforcement Learning

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