Saved in:
| Main Authors: | Sayedana, Borna, Caines, Peter E., Mahajan, Aditya |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2411.18551 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
On the Global Convergence of Policy Gradient in Average Reward Markov Decision Processes
by: Kumar, Navdeep, et al.
Published: (2024)
by: Kumar, Navdeep, et al.
Published: (2024)
Agent-state based policies in POMDPs: Beyond belief-state MDPs
by: Sinha, Amit, et al.
Published: (2024)
by: Sinha, Amit, et al.
Published: (2024)
Transmission Neural Networks: Inhibitory and Excitatory Connections
by: Gao, Shuang, et al.
Published: (2026)
by: Gao, Shuang, et al.
Published: (2026)
Online Reinforcement Learning in Markov Decision Process Using Linear Programming
by: Leon, Vincent, et al.
Published: (2023)
by: Leon, Vincent, et al.
Published: (2023)
OCMDP: Observation-Constrained Markov Decision Process
by: Wang, Taiyi, et al.
Published: (2024)
by: Wang, Taiyi, et al.
Published: (2024)
Model approximation in MDPs with unbounded per-step cost
by: Bozkurt, Berk, et al.
Published: (2024)
by: Bozkurt, Berk, et al.
Published: (2024)
Conformal Off-Policy Evaluation in Markov Decision Processes
by: Foffano, Daniele, et al.
Published: (2023)
by: Foffano, Daniele, et al.
Published: (2023)
Optimal Sample Complexity for Average Reward Markov Decision Processes
by: Wang, Shengbo, et al.
Published: (2023)
by: Wang, Shengbo, et al.
Published: (2023)
Bayesian Ambiguity Contraction-based Adaptive Robust Markov Decision Processes for Adversarial Surveillance Missions
by: Choi, Jimin, et al.
Published: (2025)
by: Choi, Jimin, et al.
Published: (2025)
Bayesian Learning of Optimal Policies in Markov Decision Processes with Countably Infinite State-Space
by: Adler, Saghar, et al.
Published: (2023)
by: Adler, Saghar, et al.
Published: (2023)
Learning Markov Processes as Sum-of-Square Forms for Analytical Belief Propagation
by: Amorese, Peter, et al.
Published: (2026)
by: Amorese, Peter, et al.
Published: (2026)
An Offline Risk-aware Policy Selection Method for Bayesian Markov Decision Processes
by: Angelotti, Giorgio, et al.
Published: (2021)
by: Angelotti, Giorgio, et al.
Published: (2021)
Finite Memory Belief Approximation for Optimal Control in Partially Observable Markov Decision Processes
by: Kim, Mintae
Published: (2026)
by: Kim, Mintae
Published: (2026)
On the Convergence of Modified Policy Iteration in Risk Sensitive Exponential Cost Markov Decision Processes
by: Murthy, Yashaswini, et al.
Published: (2023)
by: Murthy, Yashaswini, et al.
Published: (2023)
Approximate Linear Programming for Decentralized Policy Iteration in Cooperative Multi-agent Markov Decision Processes
by: Mandal, Lakshmi, et al.
Published: (2023)
by: Mandal, Lakshmi, et al.
Published: (2023)
On Convergence of Average-Reward Q-Learning in Weakly Communicating Markov Decision Processes
by: Wan, Yi, et al.
Published: (2024)
by: Wan, Yi, et al.
Published: (2024)
Improved Monte Carlo Planning via Causal Disentanglement for Structurally-Decomposed Markov Decision Processes
by: Liu, Larkin, et al.
Published: (2024)
by: Liu, Larkin, et al.
Published: (2024)
Bellman Optimality of Average-Reward Robust Markov Decision Processes with a Constant Gain
by: Wang, Shengbo, et al.
Published: (2025)
by: Wang, Shengbo, et al.
Published: (2025)
Computing the Exact Pareto Front in Average-Cost Multi-Objective Markov Decision Processes
by: Luo, Jiping, et al.
Published: (2026)
by: Luo, Jiping, et al.
Published: (2026)
1-2-3-Go! Policy Synthesis for Parameterized Markov Decision Processes via Decision-Tree Learning and Generalization
by: Azeem, Muqsit, et al.
Published: (2024)
by: Azeem, Muqsit, et al.
Published: (2024)
GenSafe: A Generalizable Safety Enhancer for Safe Reinforcement Learning Algorithms Based on Reduced Order Markov Decision Process Model
by: Zhou, Zhehua, et al.
Published: (2024)
by: Zhou, Zhehua, et al.
Published: (2024)
Differentially Private Reward Functions in Policy Synthesis for Markov Decision Processes
by: Benvenuti, Alexander, et al.
Published: (2023)
by: Benvenuti, Alexander, et al.
Published: (2023)
Robust Q-Learning under Corrupted Rewards
by: Maity, Sreejeet, et al.
Published: (2024)
by: Maity, Sreejeet, et al.
Published: (2024)
Optimistic Online LQR via Intrinsic Rewards
by: Bartos, Marcell, et al.
Published: (2026)
by: Bartos, Marcell, et al.
Published: (2026)
Quadratic Optimal Control of Graphon Q-noise Linear Systems
by: Dunyak, Alex, et al.
Published: (2024)
by: Dunyak, Alex, et al.
Published: (2024)
Transmission Neural Networks: Approximate Receding Horizon Control for Virus Spread on Networks
by: Gao, Shuang, et al.
Published: (2025)
by: Gao, Shuang, et al.
Published: (2025)
Achieving Tractable Minimax Optimal Regret in Average Reward MDPs
by: Boone, Victor, et al.
Published: (2024)
by: Boone, Victor, et al.
Published: (2024)
Low-Rank Tensors for Multi-Dimensional Markov Models
by: Navarro, Madeline, et al.
Published: (2024)
by: Navarro, Madeline, et al.
Published: (2024)
GNN-DT: Graph Neural Network Enhanced Decision Transformer for Efficient Optimization in Dynamic Environments
by: Orfanoudakis, Stavros, et al.
Published: (2025)
by: Orfanoudakis, Stavros, et al.
Published: (2025)
Identification and Adaptive Control of Markov Jump Systems: Sample Complexity and Regret Bounds
by: Sattar, Yahya, et al.
Published: (2021)
by: Sattar, Yahya, et al.
Published: (2021)
Steady-State Error Compensation for Reinforcement Learning with Quadratic Rewards
by: Wang, Liyao, et al.
Published: (2024)
by: Wang, Liyao, et al.
Published: (2024)
Guaranteeing Control Requirements via Reward Shaping in Reinforcement Learning
by: De Lellis, Francesco, et al.
Published: (2023)
by: De Lellis, Francesco, et al.
Published: (2023)
Comprehensive Overview of Reward Engineering and Shaping in Advancing Reinforcement Learning Applications
by: Ibrahim, Sinan, et al.
Published: (2024)
by: Ibrahim, Sinan, et al.
Published: (2024)
Multi-agent Multi-armed Bandits with Minimum Reward Guarantee Fairness
by: Manupriya, Piyushi, et al.
Published: (2025)
by: Manupriya, Piyushi, et al.
Published: (2025)
Finite-Time Guarantees for Multi-Agent Combinatorial Bandits with Nonstationary Rewards
by: Adams, Katherine B., et al.
Published: (2025)
by: Adams, Katherine B., et al.
Published: (2025)
Differentiable Filtering for Learning Hidden Markov Models
by: Chen, Reginald Zhiyan, et al.
Published: (2025)
by: Chen, Reginald Zhiyan, et al.
Published: (2025)
Decision-Dependent Stochastic Optimization: The Role of Distribution Dynamics
by: He, Zhiyu, et al.
Published: (2025)
by: He, Zhiyu, et al.
Published: (2025)
Learning based Modelling of Throttleable Engine Dynamics for Lunar Landing Mission
by: Kumar, Suraj, et al.
Published: (2025)
by: Kumar, Suraj, et al.
Published: (2025)
A Q-learning Approach for Adherence-Aware Recommendations
by: Faros, Ioannis, et al.
Published: (2023)
by: Faros, Ioannis, et al.
Published: (2023)
Transmission Neural Networks: Approximation and Optimal Control
by: Gao, Shuang, et al.
Published: (2025)
by: Gao, Shuang, et al.
Published: (2025)
Similar Items
-
On the Global Convergence of Policy Gradient in Average Reward Markov Decision Processes
by: Kumar, Navdeep, et al.
Published: (2024) -
Agent-state based policies in POMDPs: Beyond belief-state MDPs
by: Sinha, Amit, et al.
Published: (2024) -
Transmission Neural Networks: Inhibitory and Excitatory Connections
by: Gao, Shuang, et al.
Published: (2026) -
Online Reinforcement Learning in Markov Decision Process Using Linear Programming
by: Leon, Vincent, et al.
Published: (2023) -
OCMDP: Observation-Constrained Markov Decision Process
by: Wang, Taiyi, et al.
Published: (2024)