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Decision Making Under Uncertainty
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이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Toward Explainable Offline RL: Analyzing Representations in Intrinsically Motivated Decision Transformers
The Gittins Index: A Design Principle for Decision-Making Under Uncertainty
Q-ARDNS-Multi: A Multi-Agent Quantum Reinforcement Learning Framework with Meta-Cognitive Adaptation for Complex 3D Environments
Cognitive Guardrails for Open-World Decision Making in Autonomous Drone Swarms
Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks
Embodied AI with Foundation Models for Mobile Service Robots: A Systematic Review
Comparing Exploration-Exploitation Strategies of LLMs and Humans: Insights from Standard Multi-armed Bandit Tasks
\textsc{rfPG}: Robust Finite-Memory Policy Gradients for Hidden-Model POMDPs
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue
Recovering Event Probabilities from Large Language Model Embeddings via Axiomatic Constraints
ICNN-enhanced 2SP: Leveraging input convex neural networks for solving two-stage stochastic programming
Primal-dual algorithm for contextual stochastic combinatorial optimization
Learning Symbolic Persistent Macro-Actions for POMDP Solving Over Time
LLM-Guided Probabilistic Program Induction for POMDP Model Estimation
Wasserstein Distributionally Robust Regret Optimization
Measures of Variability for Risk-averse Policy Gradient
Towards More Efficient, Robust, Instance-adaptive, and Generalizable Sequential Decision making
Efficient Portfolio Selection through Preference Aggregation with Quicksort and the Bradley--Terry Model
Counterfactual Inference under Thompson Sampling
A friendly introduction to triangular transport
Active Inference for Energy Control and Planning in Smart Buildings and Communities
Truthful Elicitation of Imprecise Forecasts
NeuroSep-CP-LCB: A Deep Learning-based Contextual Multi-armed Bandit Algorithm with Uncertainty Quantification for Early Sepsis Prediction
Statistical Inference for Weighted Sample Average Approximation in Contextual Stochastic Optimization
Local-Global Learning of Interpretable Control Policies: The Interface between MPC and Reinforcement Learning
A Weighted Predict-and-Optimize Framework for Power System Operation Considering Varying Impacts of Uncertainty
Hierarchical Neuro-Symbolic Decision Transformer
Quantum-Inspired Reinforcement Learning in the Presence of Epistemic Ambivalence
Map Space Belief Prediction for Manipulation-Enhanced Mapping
Does Knowledge About Perceptual Uncertainty Help an Agent in Automated Driving?
Learning Fair Policies for Infectious Diseases Mitigation using Path Integral Control
Words or Numbers? How Framing Uncertainties Affects Risk Assessment and Decision-Making
Online Clustering of Dueling Bandits
Anytime Incremental $ρ$POMDP Planning in Continuous Spaces
A Model-free Biomimetics Algorithm for Deterministic Partially Observable Markov Decision Process
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