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Value Iteration

356 papers

Papers per year

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Papers

A Differential Perspective on Distributional Reinforcement Learning AAAI 2026
Methods for Optimization Problems with Markovian Stochasticity and Non-Euclidean Geometry AAAI 2026
AlphaForge: A Framework to Mine and Dynamically Combine Formulaic Alpha Factors AAAI 2025
Solving Robust Markov Decision Processes: Generic, Reliable, Efficient AAAI 2025
Towards Robust, Efficient, and Practical Decision-Making: From Reward-Maximizing Deep Reinforcement Learning to Reward-Matching GFlowNets AAAI 2025
FLAG-TRADER: Fusion LLM-Agent with Gradient-based Reinforcement Learning for Financial Trading ACL 2025
Steady-State Strategy Synthesis for Swarms of Autonomous Agents IJCAI 2025
Beyond Winning Strategies: Admissible and Admissible Winning Strategies for Quantitative Reachability Games IJCAI 2025
No Regret Reinforcement Learning Algorithms for Online Scheduling with Multi-Stage Tasks IJCAI 2025
Finite-Time Analysis of Heterogeneous Federated Temporal Difference Learning IJCAI 2025
Online Planning in MDPs with Stochastic Durative Actions IJCAI 2025
Sample Complexity of the Linear Quadratic Regulator: A Reinforcement Learning Lens JMLR 2025
Optimizing Return Distributions with Distributional Dynamic Programming JMLR 2025
Reinforcement Learning for Infinite-Dimensional Systems JMLR 2025
Reward-Directed Score-Based Diffusion Models via q-Learning JMLR 2025
Optimizing over Multiple Distributions under Generalized Quasar-Convexity Condition NIPS 2024
Gaussian Approximation and Multiplier Bootstrap for Polyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD Learning NIPS 2024
SCAFFLSA: Taming Heterogeneity in Federated Linear Stochastic Approximation and TD Learning NIPS 2024
Statistical Efficiency of Distributional Temporal Difference Learning NIPS 2024
Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm NIPS 2024
Achieving Tractable Minimax Optimal Regret in Average Reward MDPs NIPS 2024
Span-Based Optimal Sample Complexity for Weakly Communicating and General Average Reward MDPs NIPS 2024
Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning NIPS 2024
Adaptive Exploration for Data-Efficient General Value Function Evaluations NIPS 2024
Deterministic Uncertainty Propagation for Improved Model-Based Offline Reinforcement Learning NIPS 2024