A Cantor-Kantorovich Metric Between Markov Decision Processes with Application to Transfer Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Banse, Adrien, Renganathan, Venkatraman, Jungers, Raphaël M. |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Comparing Labeled Markov Chains: A Cantor-Kantorovich Approach
by: Banse, Adrien, et al.
Published: (2025)
by: Banse, Adrien, et al.
Published: (2025)
Data-driven memory-dependent abstractions of dynamical systems via a Cantor-Kantorovich metric
by: Banse, Adrien, et al.
Published: (2024)
by: Banse, Adrien, et al.
Published: (2024)
Theoretical Barriers in Bellman-Based Reinforcement Learning
by: Pinon, Brieuc, et al.
Published: (2025)
by: Pinon, Brieuc, et al.
Published: (2025)
A Generalized Bisimulation Metric of State Similarity between Markov Decision Processes: From Theoretical Propositions to Applications
by: Tao, Zhenyu, et al.
Published: (2025)
by: Tao, Zhenyu, et al.
Published: (2025)
Provably Efficient Reward Transfer in Reinforcement Learning with Discrete Markov Decision Processes
by: Vora, Kevin, et al.
Published: (2025)
by: Vora, Kevin, et al.
Published: (2025)
Optimal Decision Tree Policies for Markov Decision Processes
by: Vos, Daniël, et al.
Published: (2023)
by: Vos, Daniël, et al.
Published: (2023)
Act as You Learn: Adaptive Decision-Making in Non-Stationary Markov Decision Processes
by: Luo, Baiting, et al.
Published: (2024)
by: Luo, Baiting, et al.
Published: (2024)
Markov Decision Processes under External Temporal Processes
by: Ayyagari, Ranga Shaarad, et al.
Published: (2023)
by: Ayyagari, Ranga Shaarad, et al.
Published: (2023)
Optimistic Regret Bounds for Online Learning in Adversarial Markov Decision Processes
by: Moon, Sang Bin, et al.
Published: (2024)
by: Moon, Sang Bin, et al.
Published: (2024)
Diffusion-Augmented Markov Decision Processes for Maximum Entropy Reinforcement Learning
by: Sanokowski, Sebastian, et al.
Published: (2025)
by: Sanokowski, Sebastian, et al.
Published: (2025)
Policy Gradient for Robust Markov Decision Processes
by: Wang, Qiuhao, et al.
Published: (2024)
by: Wang, Qiuhao, et al.
Published: (2024)
Federated Learning with Differential Privacy
by: Banse, Adrien, et al.
Published: (2024)
by: Banse, Adrien, et al.
Published: (2024)
Globally Optimal Hierarchical Reinforcement Learning for Linearly-Solvable Markov Decision Processes
by: Infante, Guillermo, et al.
Published: (2021)
by: Infante, Guillermo, et al.
Published: (2021)
Policy Gradient Algorithms with Monte Carlo Tree Learning for Non-Markov Decision Processes
by: Morimura, Tetsuro, et al.
Published: (2022)
by: Morimura, Tetsuro, et al.
Published: (2022)
Reinforcement Learning in Switching Non-Stationary Markov Decision Processes: Algorithms and Convergence Analysis
by: Amiri, Mohsen, et al.
Published: (2025)
by: Amiri, Mohsen, et al.
Published: (2025)
A Unified Theory of Compositionality, Modularity, and Interpretability in Markov Decision Processes
by: Ringstrom, Thomas J., et al.
Published: (2025)
by: Ringstrom, Thomas J., et al.
Published: (2025)
Solving Robust Markov Decision Processes: Generic, Reliable, Efficient
by: Meggendorfer, Tobias, et al.
Published: (2024)
by: Meggendorfer, Tobias, et al.
Published: (2024)
Hierarchical Average-Reward Linearly-solvable Markov Decision Processes
by: Infante, Guillermo, et al.
Published: (2024)
by: Infante, Guillermo, et al.
Published: (2024)
SPOT: Scalable Policy Optimization with Trees for Markov Decision Processes
by: Xiong, Xuyuan, et al.
Published: (2025)
by: Xiong, Xuyuan, et al.
Published: (2025)
Task Aware Modulation using Representation Learning: An Approach for Few Shot Learning in Environmental Systems
by: Renganathan, Arvind, et al.
Published: (2023)
by: Renganathan, Arvind, et al.
Published: (2023)
Almost Sure Convergence of Differential Temporal Difference Learning for Average Reward Markov Decision Processes
by: Blaser, Ethan, et al.
Published: (2026)
by: Blaser, Ethan, et al.
Published: (2026)
Linear Mixture Distributionally Robust Markov Decision Processes
by: Liu, Zhishuai, et al.
Published: (2025)
by: Liu, Zhishuai, et al.
Published: (2025)
Efficient and Sharp Off-Policy Evaluation in Robust Markov Decision Processes
by: Bennett, Andrew, et al.
Published: (2024)
by: Bennett, Andrew, et al.
Published: (2024)
Homomorphic Mappings for Value-Preserving State Aggregation in Markov Decision Processes
by: Zhao, Shuo, et al.
Published: (2025)
by: Zhao, Shuo, et al.
Published: (2025)
Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes
by: Kumar, Navdeep, et al.
Published: (2025)
by: Kumar, Navdeep, et al.
Published: (2025)
OCMDP: Observation-Constrained Markov Decision Process
by: Wang, Taiyi, et al.
Published: (2024)
by: Wang, Taiyi, et al.
Published: (2024)
Rethinking Large Language Model Distillation: A Constrained Markov Decision Process Perspective
by: Zimmer, Matthieu, et al.
Published: (2025)
by: Zimmer, Matthieu, et al.
Published: (2025)
REValueD: Regularised Ensemble Value-Decomposition for Factorisable Markov Decision Processes
by: Ireland, David, et al.
Published: (2024)
by: Ireland, David, et al.
Published: (2024)
MATE: Solving Contextual Markov Decision Processes with Memory of Accumulated Transition Embeddings
by: Hwang, Himchan, et al.
Published: (2026)
by: Hwang, Himchan, et al.
Published: (2026)
Policy Regularized Distributionally Robust Markov Decision Processes with Linear Function Approximation
by: Gu, Jingwen, et al.
Published: (2025)
by: Gu, Jingwen, et al.
Published: (2025)
Burning RED: Unlocking Subtask-Driven Reinforcement Learning and Risk-Awareness in Average-Reward Markov Decision Processes
by: Rojas, Juan Sebastian, et al.
Published: (2024)
by: Rojas, Juan Sebastian, 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)
Regret Analysis of Policy Gradient Algorithm for Infinite Horizon Average Reward Markov Decision Processes
by: Bai, Qinbo, et al.
Published: (2023)
by: Bai, Qinbo, et al.
Published: (2023)
Deep Reinforcement Learning for Personalized Diagnostic Decision Pathways Using Electronic Health Records: A Comparative Study on Anemia and Systemic Lupus Erythematosus
by: Muyama, Lillian, et al.
Published: (2024)
by: Muyama, Lillian, et al.
Published: (2024)
Kov: Transferable and Naturalistic Black-Box LLM Attacks using Markov Decision Processes and Tree Search
by: Moss, Robert J.
Published: (2024)
by: Moss, Robert J.
Published: (2024)
Robust Lagrangian and Adversarial Policy Gradient for Robust Constrained Markov Decision Processes
by: Bossens, David M.
Published: (2023)
by: Bossens, David M.
Published: (2023)
Observation Adaptation via Annealed Importance Resampling for Partially Observable Markov Decision Processes
by: Zhang, Yunuo, et al.
Published: (2025)
by: Zhang, Yunuo, et al.
Published: (2025)
Structural Estimation of Markov Decision Processes in High-Dimensional State Space with Finite-Time Guarantees
by: Zeng, Siliang, et al.
Published: (2022)
by: Zeng, Siliang, et al.
Published: (2022)
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)
Decision-Focused Model-based Reinforcement Learning for Reward Transfer
by: Sharma, Abhishek, et al.
Published: (2023)
by: Sharma, Abhishek, et al.
Published: (2023)
Similar Items
-
Comparing Labeled Markov Chains: A Cantor-Kantorovich Approach
by: Banse, Adrien, et al.
Published: (2025) -
Data-driven memory-dependent abstractions of dynamical systems via a Cantor-Kantorovich metric
by: Banse, Adrien, et al.
Published: (2024) -
Theoretical Barriers in Bellman-Based Reinforcement Learning
by: Pinon, Brieuc, et al.
Published: (2025) -
A Generalized Bisimulation Metric of State Similarity between Markov Decision Processes: From Theoretical Propositions to Applications
by: Tao, Zhenyu, et al.
Published: (2025) -
Provably Efficient Reward Transfer in Reinforcement Learning with Discrete Markov Decision Processes
by: Vora, Kevin, et al.
Published: (2025)