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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/shengroup/fedigw

공식 코드

Harnessing the Power of Federated Learning in Federated Contextual Bandits

https://github.com/shengzhang37/SAVE

공식 코드

Statistical Inference of the Value Function for Reinforcement Learning in Infinite Horizon Settings

https://github.com/shshnkreddy/deceptiverl

공식 코드

Preserving the Privacy of Reward Functions in MDPs through Deception

https://github.com/shukla-yash/lsts-icaps-24

공식 코드

Logical Specifications-guided Dynamic Task Sampling for Reinforcement Learning Agents

https://github.com/sisl/AutomotivePOMDPs.jl

공식 코드

Decomposition Methods with Deep Corrections for Reinforcement Learning

https://github.com/sisl/DreamrHHP

공식 코드

Dynamic Real-time Multimodal Routing with Hierarchical Hybrid Planning

https://github.com/sisl/POMDPStressTesting.jl

공식 코드

Adaptive Stress Testing of Trajectory Predictions in Flight Management Systems

https://github.com/sisl/SCoBA.jl

공식 코드

Dynamic Multi-Robot Task Allocation under Uncertainty and Temporal Constraints

https://github.com/sisl/ventilators

공식 코드

Optimal Control of Mechanical Ventilators with Learned Respiratory Dynamics

https://github.com/siyan-zhao/decision-stacks

공식 코드

Decision Stacks: Flexible Reinforcement Learning via Modular Generative Models

https://github.com/sjgershm/exploration

공식 코드

Comparing Exploration-Exploitation Strategies of LLMs and Humans: Insights from Standard Multi-armed Bandit Tasks

https://github.com/sjunges/shielding-POMDPs

공식 코드

Enforcing Almost-Sure Reachability in POMDPs

https://github.com/sjyucnel/conditional_cs_divergence

공식 코드

The Conditional Cauchy-Schwarz Divergence with Applications to Time-Series Data and Sequential Decision Making

https://github.com/skandavaidyanath/credit-assignment

공식 코드

Hindsight-DICE: Stable Credit Assignment for Deep Reinforcement Learning

https://github.com/skyriver-2000/trad-official

공식 코드

TRAD: Enhancing LLM Agents with Step-Wise Thought Retrieval and Aligned Decision

https://github.com/snurkabill/MasterThesis

공식 코드

Reinforcement Learning of Risk-Constrained Policies in Markov Decision Processes

https://github.com/ssg-research/flare

공식 코드

FLARE: Fingerprinting Deep Reinforcement Learning Agents using Universal Adversarial Masks

https://github.com/stelios30/agent-specific-effects

공식 코드

Agent-Specific Effects: A Causal Effect Propagation Analysis in Multi-Agent MDPs

https://github.com/stelios30/cf-effect-decomposition

공식 코드

Counterfactual Effect Decomposition in Multi-Agent Sequential Decision Making

https://github.com/stratosphereips/netsecgame

공식 코드

Out of the Cage: How Stochastic Parrots Win in Cyber Security Environments

https://github.com/swyoon/value-gradient-sampler

공식 코드

Value Gradient Sampler: Sampling as Sequential Decision Making

https://github.com/sycny/Awesome-Trustworthy-GUI-Agents

공식 코드

Towards Trustworthy GUI Agents: A Survey

https://github.com/szrlee/GPT-HyperAgent

공식 코드

Scalable Exploration via Ensemble++

https://github.com/szrlee/ensemble_plus_plus

공식 코드

Scalable Exploration via Ensemble++

https://github.com/tajwarfahim/paprika

공식 코드

Training a Generally Curious Agent

https://github.com/taodav/aux-inputs

공식 코드

Agent-State Construction with Auxiliary Inputs

https://github.com/theovincent/pbo

공식 코드

Parameterized Projected Bellman Operator

https://github.com/thibauttheate/risk-sensitive-policy-with-distributional-reinforcement-learning

공식 코드

Risk-Sensitive Policy with Distributional Reinforcement Learning

https://github.com/tianxiangzhao/imitationnoisydemon

공식 코드

Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations

https://github.com/tingstat/Data_Combination

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Combining Experimental and Historical Data for Policy Evaluation

https://github.com/tomsilver/pddlgym

공식 코드

PDDLGym: Gym Environments from PDDL Problems

https://github.com/toshihiro-ota/decision-mamba

공식 코드

Decision Mamba: Reinforcement Learning via Sequence Modeling with Selective State Spaces

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

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Automaton-Guided Curriculum Generation for Reinforcement Learning Agents

https://github.com/tumbais/hybridmadrl-amod

공식 코드

Hybrid Multi-agent Deep Reinforcement Learning for Autonomous Mobility on Demand Systems

https://github.com/tumbais/hybridmadrl-amod-relocation

공식 코드

Multi-Agent Soft Actor-Critic with Coordinated Loss for Autonomous Mobility-on-Demand Fleet Control

https://github.com/tung-nd/tnp-pytorch

공식 코드

Transformer Neural Processes: Uncertainty-Aware Meta Learning Via Sequence Modeling

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