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Sequential Decision Making

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Showing 601–650 of 1210 papers

TitleStatusHype
Blessing from Human-AI Interaction: Super Reinforcement Learning in Confounded Environments—0
Modeling driver's evasive behavior during safety-critical lane changes:Two-dimensional time-to-collision and deep reinforcement learning—0
Optimistic MLE -- A Generic Model-based Algorithm for Partially Observable Sequential Decision Making—0
Reinforcement Learning with Non-Exponential Discounting—0
On Efficient Online Imitation Learning via Classification—0
Deep Reinforcement Learning for Adaptive Mesh Refinement—0
Non-monotonic Resource Utilization in the Bandits with Knapsacks ProblemCode0
Graph Neural Networks for Multi-Robot Active Information Acquisition—0
SCALES: From Fairness Principles to Constrained Decision-MakingCode0
Batch Bayesian optimisation via density-ratio estimation with guaranteesCode0
Thompson Sampling with Virtual Helping Agents—0
A Survey on Large-Population Systems and Scalable Multi-Agent Reinforcement Learning—0
Sequential Information Design: Learning to Persuade in the Dark—0
MetaTrader: An Reinforcement Learning Approach Integrating Diverse Policies for Portfolio Optimization—0
Federated Online Clustering of BanditsCode0
JARVIS: A Neuro-Symbolic Commonsense Reasoning Framework for Conversational Embodied Agents—0
Entropy Regularization for Population Estimation—0
Sampling Through the Lens of Sequential Decision Making—0
Streaming Adaptive Submodular Maximization—0
Understanding the stochastic dynamics of sequential decision-making processes: A path-integral analysis of multi-armed bandits—0
Deep VULMAN: A Deep Reinforcement Learning-Enabled Cyber Vulnerability Management Framework—0
A Bayesian Approach to Learning Bandit Structure in Markov Decision Processes—0
Sample-efficient Safe Learning for Online Nonlinear Control with Control Barrier Functions—0
Branch Ranking for Efficient Mixed-Integer Programming via Offline Ranking-based Policy Learning—0
Partial-Monotone Adaptive Submodular Maximization—0
Adaptive Asynchronous Control Using Meta-learned Neural Ordinary Differential Equations—0
High dimensional stochastic linear contextual bandit with missing covariates—0
Learn Continuously, Act Discretely: Hybrid Action-Space Reinforcement Learning For Optimal Execution—0
Strategising template-guided needle placement for MR-targeted prostate biopsy—0
Delayed Feedback in Generalised Linear Bandits Revisited—0
Online Learning with Off-Policy Feedback—0
Guaranteed Discovery of Control-Endogenous Latent States with Multi-Step Inverse Models—0
Hindsight Learning for MDPs with Exogenous InputsCode0
Contextual Bandits with Large Action Spaces: Made PracticalCode0
Scaling up ML-based Black-box Planning with Partial STRIPS Models—0
Improving saliency models' predictions of the next fixation with humans' intrinsic cost of gaze shifts—0
Transformer Neural Processes: Uncertainty-Aware Meta Learning Via Sequence ModelingCode1
Learning Optimal Solutions via an LSTM-Optimization Framework—0
Reinforcement Learning Approaches for the Orienteering Problem with Stochastic and Dynamic Release Dates—0
Reinforcement Learning Based Dynamic Model Combination for Time Series Forecasting—0
Utility Theory for Sequential Decision Making—0
Estimating Link Flows in Road Networks with Synthetic Trajectory Data Generation: Reinforcement Learning-based Approaches—0
A Survey on Model-based Reinforcement Learning—0
Federated Learning with Uncertainty via Distilled Predictive Distributions—0
Interactively Learning Preference Constraints in Linear BanditsCode0
Adaptive Rollout Length for Model-Based RL Using Model-Free Deep RL—0
Convergence and sample complexity of natural policy gradient primal-dual methods for constrained MDPs—0
Deciding What to Model: Value-Equivalent Sampling for Reinforcement Learning—0
Interpolating Between Softmax Policy Gradient and Neural Replicator Dynamics with Capped Implicit Exploration—0
Between Rate-Distortion Theory & Value Equivalence in Model-Based Reinforcement Learning—0
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