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Sequential Decision Making

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코드

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

https://github.com/zhaohaoru/federated-clustering-of-bandits

공식 코드

Federated Online Clustering of Bandits

https://github.com/zhaoyi11/tcrl

공식 코드

Simplified Temporal Consistency Reinforcement Learning

https://github.com/zhaoyizhou1123/mbrcsl

공식 코드

Free from Bellman Completeness: Trajectory Stitching via Model-based Return-conditioned Supervised Learning

https://github.com/zifanwu/plan-to-predict

공식 코드

Plan To Predict: Learning an Uncertainty-Foreseeing Model for Model-Based Reinforcement Learning

https://github.com/ziyadsheeba/qfat

공식 코드

Quantization-Free Autoregressive Action Transformer

https://github.com/zjduan/abplanner

공식 코드

An Adaptable Budget Planner for Enhancing Budget-Constrained Auto-Bidding in Online Advertising

https://github.com/zjlab-ammi/llm4rl

공식 코드

Enabling Intelligent Interactions between an Agent and an LLM: A Reinforcement Learning Approach

https://github.com/zjlab-ammi/llm4teach

공식 코드

Large Language Model as a Policy Teacher for Training Reinforcement Learning Agents

https://github.com/Denbergvanthijs/imbDRL

Deep Reinforcement Learning for Imbalanced Classification

https://github.com/Driesssens/ibp-pytorch

Learning model-based planning from scratch

https://github.com/Finspire13/RL-Surgical-Gesture-Segmentation

Deep Reinforcement Learning for Surgical Gesture Segmentation and Classification

https://github.com/HoganZhang/pytorch-vsumm-reinforce

Deep Reinforcement Learning for Unsupervised Video Summarization with Diversity-Representativeness Reward

https://github.com/Kaixhin/EC

Model-Free Episodic Control

https://github.com/KaiyangZhou/pytorch-vsumm-reinforce

Deep Reinforcement Learning for Unsupervised Video Summarization with Diversity-Representativeness Reward

https://github.com/Kikumu/Reinforcement-Learning-repo

Reinforcement Learning

https://github.com/LucaMaurici/MultiHop-Reading-Comprehension-DRL

Multi-hop Reading Comprehension via Deep Reinforcement Learning based Document Traversal

https://github.com/MilkSilk/masters_thesis

IQ-Learn: Inverse soft-Q Learning for Imitation

https://github.com/Montherapy/Deep-reinforcement-learning-for-multi-class-imbalanced-classification

Deep Reinforcement Learning for Imbalanced Classification

https://github.com/PlaytikaOSS/pybandits

Doubly Robust Policy Evaluation and Optimization

https://github.com/RunzheStat/TestMDP

Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making

https://github.com/ScottJordan/SafePolicyImprovementNonstationary

Towards Safe Policy Improvement for Non-Stationary MDPs

https://github.com/Shalev-Lifshitz/STEVE-1

STEVE-1: A Generative Model for Text-to-Behavior in Minecraft

https://github.com/ShibiHe/Model-Free-Episodic-Control

Model-Free Episodic Control

https://github.com/UnibucProjects/DeepRLRecommenderSystem

Deep Reinforcement Learning based Recommendation with Explicit User-Item Interactions Modeling

https://github.com/VinAIResearch/PCC-pytorch

Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control

https://github.com/VirgiAgl/DAG-GP

Multi-task Causal Learning with Gaussian Processes

https://github.com/WuJie1010/Temporally-language-grounding

Read, Watch, and Move: Reinforcement Learning for Temporally Grounding Natural Language Descriptions in Videos

https://github.com/Xi-Liu/heteroscedasticbandits

Stay With Me: Lifetime Maximization Through Heteroscedastic Linear Bandits With Reneging

https://github.com/aashish-khub/NearestNeighbors

On adaptivity and minimax optimality of two-sided nearest neighbors

https://github.com/azfeng8/pddlgym

PDDLGym: Gym Environments from PDDL Problems

https://github.com/backgom2357/Recommender_system_via_deep_RL

Deep Reinforcement Learning based Recommendation with Explicit User-Item Interactions Modeling

https://github.com/ben-ix/multiagentmarkets

Bounded rationality for relaxing best response and mutual consistency: The Quantal Hierarchy model of decision-making

https://github.com/bluelancer/SANDWICH

SANDWICH: Towards an Offline, Differentiable, Fully-Trainable Wireless Neural Ray-Tracing Surrogate

https://github.com/bruzwen/ddxplus

Efficient Symptom Inquiring and Diagnosis via Adaptive Alignment of Reinforcement Learning and Classification

https://github.com/cognitiveailab/textworldexpress

Text-based RL Agents with Commonsense Knowledge: New Challenges, Environments and Baselines

https://github.com/coreylowman/ragz

Thinking Fast and Slow with Deep Learning and Tree Search

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