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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/XanderJC/medkit-learn

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The Medkit-Learn(ing) Environment: Medical Decision Modelling through Simulation

https://github.com/YoshikiKubotani/rltutor

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RLTutor: Reinforcement Learning Based Adaptive Tutoring System by Modeling Virtual Student with Fewer Interactions

https://github.com/Yuantian013/Sym-Q

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Sym-Q: Adaptive Symbolic Regression via Sequential Decision-Making

https://github.com/ZONG0004/MacroHFT

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MacroHFT: Memory Augmented Context-aware Reinforcement Learning On High Frequency Trading

https://github.com/Zhendong-Wang/Thompson-Sampling-via-Local-Uncertainty

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Thompson Sampling via Local Uncertainty

https://github.com/Zhengbo-Zhang/ITKD

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Instance Temperature Knowledge Distillation

https://github.com/aair-lab/grapl

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Epistemic Exploration for Generalizable Planning and Learning in Non-Stationary Settings

https://github.com/aair-lab/qace

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Autonomous Capability Assessment of Sequential Decision-Making Systems in Stochastic Settings (Extended Version)

https://github.com/abhi460729/Action-Duration-with-Contextual-Bandits-for-Deep-Reinforcement-Learning-in-Dynamic-Environments

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Adaptive Action Duration with Contextual Bandits for Deep Reinforcement Learning in Dynamic Environments

https://github.com/adaruna3/explainable-kge

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Explainable Knowledge Graph Embedding: Inference Reconciliation for Knowledge Inferences Supporting Robot Actions

https://github.com/adishs/neurips2021_curriculum-teaching-demonstrations_code

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Curriculum Design for Teaching via Demonstrations: Theory and Applications

https://github.com/agentification/language-integrated-vi

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How Can LLM Guide RL? A Value-Based Approach

https://github.com/aidaafshar/delf

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DeLF: Designing Learning Environments with Foundation Models

https://github.com/alcedok/SocialNav_paper

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Perspective-Shifted Neuro-Symbolic World Models: A Framework for Socially-Aware Robot Navigation

https://github.com/aleksa-sukovic/iclr2024-reward-design-for-justifiable-rl

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Reward Design for Justifiable Sequential Decision-Making

https://github.com/alex-yanranwang/awavo

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Probabilistic Constrained Reinforcement Learning with Formal Interpretability

https://github.com/alextzik/distribution_steering_MDP

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Discrete-Time Distribution Steering using Monte Carlo Tree Search

https://github.com/alinlab/oreo

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Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning

https://github.com/allenai/rl4lms

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Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization

https://github.com/allenai/sso

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Skill Set Optimization: Reinforcing Language Model Behavior via Transferable Skills

https://github.com/alstn12088/adaptive-teacher

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Adaptive teachers for amortized samplers

https://github.com/altundasbatu/HybridNet_IROS2022

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Learning Coordination Policies over Heterogeneous Graphs for Human-Robot Teams via Recurrent Neural Schedule Propagation

https://github.com/andrei-t-neagu/drl_in_finance

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Deep Reinforcement Learning Algorithms for Option Hedging

https://github.com/andrew-j-levy/Hierarchical-Actor-Critc-HAC-

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Learning Multi-Level Hierarchies with Hindsight

https://github.com/andrewli77/reward-machines-noisy-environments

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Reward Machines for Deep RL in Noisy and Uncertain Environments

https://github.com/annadeichler/tree-rl-adaptive

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Think Too Fast Nor Too Slow: The Computational Trade-off Between Planning And Reinforcement Learning

https://github.com/anonymousresearcher5642/functionencoderrl

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Zero-Shot Reinforcement Learning via Function Encoders

https://github.com/anqili/mahalo

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MAHALO: Unifying Offline Reinforcement Learning and Imitation Learning from Observations

https://github.com/archo48/nmpa

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Learning Non-myopic Power Allocation in Constrained Scenarios

https://github.com/aria-systems-group/hsvi-rp

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Sound Heuristic Search Value Iteration for Undiscounted POMDPs with Reachability Objectives

https://github.com/artificial-memory-lab/optimist-router

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Optimistic Query Routing in Clustering-based Approximate Maximum Inner Product Search

https://github.com/bach1292/KDD_Cup_2019_LOLS_Team

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Policy Learning for Malaria Control

https://github.com/baitingluo/l-map

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Scalable Decision-Making in Stochastic Environments through Learned Temporal Abstraction

https://github.com/bhouri0412/rpn_bo

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Scalable Bayesian optimization with high-dimensional outputs using randomized prior networks

https://github.com/bit1029public/ADRQN

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On Improving Deep Reinforcement Learning for POMDPs

https://github.com/blyucs/autogmap

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AutoGMap: Learning to Map Large-scale Sparse Graphs on Memristive Crossbars

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