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Sequential Decision Making

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Showing 601–650 of 1210 papers

TitleStatusHype
Patterns, predictions, and actions: A story about machine learning—0
PDQN - A Deep Reinforcement Learning Method for Planning with Long Delays: Optimization of Manufacturing Dispatching—0
Pessimistic Model Selection for Offline Deep Reinforcement Learning—0
Planning with General Objective Functions: Going Beyond Total Rewards—0
Playing against Nature: causal discovery for decision making under uncertainty—0
POLAR: A Pessimistic Model-based Policy Learning Algorithm for Dynamic Treatment Regimes—0
Mean-Variance Efficient Reinforcement Learning with Applications to Dynamic Financial Investment—0
Policy Gradient With Value Function Approximation For Collective Multiagent Planning—0
Policy-labeled Preference Learning: Is Preference Enough for RLHF?—0
Population-based Evaluation in Repeated Rock-Paper-Scissors as a Benchmark for Multiagent Reinforcement Learning—0
Position Paper: Rethinking Privacy in RL for Sequential Decision-making in the Age of LLMs—0
Predicting and Understanding Human Action Decisions: Insights from Large Language Models and Cognitive Instance-Based Learning—0
Predicting Periodicity with Temporal Difference Learning—0
Learning-to-defer for sequential medical decision-making under uncertainty—0
Preference at First Sight—0
Preference Optimization as Probabilistic Inference—0
Reference Points, Risk-Taking Behavior, and Competitive Outcomes in Sequential Settings—0
Privacy-Constrained Policies via Mutual Information Regularized Policy Gradients—0
Probabilistic DAG Search—0
Probability Tools for Sequential Random Projection—0
Proportional Aggregation of Preferences for Sequential Decision Making—0
Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes—0
Provable Reinforcement Learning with a Short-Term Memory—0
PROVABLY BENEFITS OF DEEP HIERARCHICAL RL—0
Provably Efficient Causal Model-Based Reinforcement Learning for Systematic Generalization—0
Provably Efficient Reinforcement Learning for Adversarial Restless Multi-Armed Bandits with Unknown Transitions and Bandit Feedback—0
Provably Efficient UCB-type Algorithms For Learning Predictive State Representations—0
Provably Learning Nash Policies in Constrained Markov Potential Games—0
Proximal Reinforcement Learning: A New Theory of Sequential Decision Making in Primal-Dual Spaces—0
Pure Exploration under Mediators' Feedback—0
QForce-RL: Quantized FPGA-Optimized Reinforcement Learning Compute Engine—0
Q-LDA: Uncovering Latent Patterns in Text-based Sequential Decision Processes—0
Q-learning with temporal memory to navigate turbulence—0
Quantile Off-Policy Evaluation via Deep Conditional Generative Learning—0
Quantum deep recurrent reinforcement learning—0
Quantum Reinforcement Learning-Based Two-Stage Unit Commitment Framework for Enhanced Power Systems Robustness—0
RAISE: Reinforenced Adaptive Instruction Selection For Large Language Models—0
Real-Time Web Scale Event Summarization Using Sequential Decision Making—0
Reasoning in visual navigation of end-to-end trained agents: a dynamical systems approach—0
Recent Advances in Leveraging Human Guidance for Sequential Decision-Making Tasks—0
Rectifying Reinforcement Learning for Reward Matching—0
Reducing Planning Complexity of General Reinforcement Learning with Non-Markovian Abstractions—0
Regret and Cumulative Constraint Violation Analysis for Distributed Online Constrained Convex Optimization—0
Regret Bounds for Online Portfolio Selection with a Cardinality Constraint—0
Regret-Minimization Algorithms for Multi-Agent Cooperative Learning Systems—0
Regret Minimization via Saddle Point Optimization—0
Regular Decision Processes for Grid Worlds—0
Regularized Conditional Diffusion Model for Multi-Task Preference Alignment—0
Regularized Q-Learning with Linear Function Approximation—0
Reinforced Approximate Exploratory Data Analysis—0
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