Papers with Code 아카이브

General Reinforcement Learning

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하위 태스크: 2
평가표: 6
보존된 평가 기록: 12

코드

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

https://github.com/securitygames/oef

공식 코드

Offline Equilibrium Finding

https://github.com/seohongpark/fql

공식 코드

Flow Q-Learning

https://github.com/seohongpark/pma

공식 코드

Predictable MDP Abstraction for Unsupervised Model-Based RL

https://github.com/sfujim/TD3_BC

공식 코드

A Minimalist Approach to Offline Reinforcement Learning

https://github.com/shagunsodhani/consistent-dynamics

공식 코드

Learning Powerful Policies by Using Consistent Dynamics Model

https://github.com/sharadmv/parasol

공식 코드

SOLAR: Deep Structured Representations for Model-Based Reinforcement Learning

https://github.com/sharkwyf/cgdt

공식 코드

Critic-Guided Decision Transformer for Offline Reinforcement Learning

https://github.com/shentao-yang/ampl_neurips2022

공식 코드

A Unified Framework for Alternating Offline Model Training and Policy Learning

https://github.com/shentao-yang/sdm-gan_icml2022

공식 코드

Regularizing a Model-based Policy Stationary Distribution to Stabilize Offline Reinforcement Learning

https://github.com/shlee94/Off2OnRL

공식 코드

Offline-to-Online Reinforcement Learning via Balanced Replay and Pessimistic Q-Ensemble

https://github.com/shripaddeshmukh/xrl_with_trajectories

공식 코드

Explaining RL Decisions with Trajectories

https://github.com/si0wang/pdml

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Live in the Moment: Learning Dynamics Model Adapted to Evolving Policy

https://github.com/siddharthverma314/chai-naacl-2022

공식 코드

CHAI: A CHatbot AI for Task-Oriented Dialogue with Offline Reinforcement Learning

https://github.com/siemens/industrialbenchmark

공식 코드

Learning and Policy Search in Stochastic Dynamical Systems with Bayesian Neural Networks

https://github.com/siemens/policy_search_bb-alpha

공식 코드

Learning and Policy Search in Stochastic Dynamical Systems with Bayesian Neural Networks

https://github.com/sildater/parangonar

공식 코드

Online Symbolic Music Alignment with Offline Reinforcement Learning

https://github.com/sirabas369/diffclone

공식 코드

DiffClone: Enhanced Behaviour Cloning in Robotics with Diffusion-Driven Policy Learning

https://github.com/sisl/mechamodlearn

공식 코드

A General Framework for Structured Learning of Mechanical Systems

https://github.com/skezle/continual-dreamer

공식 코드

The Effectiveness of World Models for Continual Reinforcement Learning

https://github.com/snu-mllab/dppo

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Direct Preference-based Policy Optimization without Reward Modeling

https://github.com/spitis/mocoda

공식 코드

MoCoDA: Model-based Counterfactual Data Augmentation

https://github.com/srzer/LaMo-2023

공식 코드

Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning

https://github.com/stavrosorf/dt4evs

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GNN-DT: Graph Neural Network Enhanced Decision Transformer for Efficient Optimization in Dynamic Environments

https://github.com/stillwolf/acsf-snn

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A Low Latency Adaptive Coding Spiking Framework for Deep Reinforcement Learning

https://github.com/stratosphereips/meme_malware_rl

공식 코드

The Power of MEME: Adversarial Malware Creation with Model-Based Reinforcement Learning

https://github.com/sweetice/POPO

공식 코드

POPO: Pessimistic Offline Policy Optimization

https://github.com/sweety-dm/interference-aware-deep-q-learning

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Catastrophic Interference in Reinforcement Learning: A Solution Based on Context Division and Knowledge Distillation

https://github.com/syscv/trafficbots

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TrafficBots: Towards World Models for Autonomous Driving Simulation and Motion Prediction

https://github.com/syyunn/finrl-dt

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Pretrained LLM Adapted with LoRA as a Decision Transformer for Offline RL in Quantitative Trading

https://github.com/t6-thu/H2O

공식 코드

When to Trust Your Simulator: Dynamics-Aware Hybrid Offline-and-Online Reinforcement Learning

https://github.com/takuseno/d3rlpy

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d3rlpy: An Offline Deep Reinforcement Learning Library

https://github.com/taochenshh/exp4nav

공식 코드

Learning Exploration Policies for Navigation

https://github.com/tencent-ailab/hokoff

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Hokoff: Real Game Dataset from Honor of Kings and its Offline Reinforcement Learning Benchmarks

https://github.com/tensorflow/tensor2tensor

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Model-Based Reinforcement Learning for Atari

https://github.com/thanard/me-trpo

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Model-Ensemble Trust-Region Policy Optimization

https://github.com/thanhnguyentang/drbqo

공식 코드

On Practical Reinforcement Learning: Provable Robustness, Scalability, and Statistical Efficiency

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