Cover Image

A Generalized Bisimulation Metric of State Similarity between Markov Decision Processes: From Theoretical Propositions to Applications

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Tao, Zhenyu, Xu, Wei, You, Xiaohu
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Theoretical Analysis of State Similarity Between Markov Decision Processes
by: Tao, Zhenyu, et al.
Published: (2025)

Provable Performance Bounds for Digital Twin-driven Deep Reinforcement Learning in Wireless Networks: A Novel Digital-Twin Bisimulation Metric
by: Tao, Zhenyu, et al.
Published: (2025)

A Cantor-Kantorovich Metric Between Markov Decision Processes with Application to Transfer Learning
by: Banse, Adrien, et al.
Published: (2024)

Policy Gradient for Robust Markov Decision Processes
by: Wang, Qiuhao, et al.
Published: (2024)

Homomorphic Mappings for Value-Preserving State Aggregation in Markov Decision Processes
by: Zhao, Shuo, et al.
Published: (2025)

Solving Robust Markov Decision Processes: Generic, Reliable, Efficient
by: Meggendorfer, Tobias, et al.
Published: (2024)

Optimal Decision Tree Policies for Markov Decision Processes
by: Vos, Daniël, et al.
Published: (2023)

Linear Mixture Distributionally Robust Markov Decision Processes
by: Liu, Zhishuai, et al.
Published: (2025)

Markov Decision Processes under External Temporal Processes
by: Ayyagari, Ranga Shaarad, et al.
Published: (2023)

Policy Regularized Distributionally Robust Markov Decision Processes with Linear Function Approximation
by: Gu, Jingwen, et al.
Published: (2025)

Map2Traj: Street Map Piloted Zero-shot Trajectory Generation with Diffusion Model
by: Tao, Zhenyu, et al.
Published: (2024)

A Unified Theory of Compositionality, Modularity, and Interpretability in Markov Decision Processes
by: Ringstrom, Thomas J., et al.
Published: (2025)

SPOT: Scalable Policy Optimization with Trees for Markov Decision Processes
by: Xiong, Xuyuan, et al.
Published: (2025)

Act as You Learn: Adaptive Decision-Making in Non-Stationary Markov Decision Processes
by: Luo, Baiting, et al.
Published: (2024)

Hierarchical Average-Reward Linearly-solvable Markov Decision Processes
by: Infante, Guillermo, et al.
Published: (2024)

Structural Estimation of Markov Decision Processes in High-Dimensional State Space with Finite-Time Guarantees
by: Zeng, Siliang, et al.
Published: (2022)

Diffusion-Augmented Markov Decision Processes for Maximum Entropy Reinforcement Learning
by: Sanokowski, Sebastian, et al.
Published: (2025)

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes
by: Kumar, Navdeep, et al.
Published: (2025)

Efficient and Sharp Off-Policy Evaluation in Robust Markov Decision Processes
by: Bennett, Andrew, et al.
Published: (2024)

Optimistic Regret Bounds for Online Learning in Adversarial Markov Decision Processes
by: Moon, Sang Bin, et al.
Published: (2024)

Propositional Logic for Probing Generalization in Neural Networks
by: Langedijk, Anna, et al.
Published: (2025)

OCMDP: Observation-Constrained Markov Decision Process
by: Wang, Taiyi, et al.
Published: (2024)

Stable Offline Value Function Learning with Bisimulation-based Representations
by: Pavse, Brahma S., et al.
Published: (2024)

Rethinking Large Language Model Distillation: A Constrained Markov Decision Process Perspective
by: Zimmer, Matthieu, et al.
Published: (2025)

Provably Efficient Reward Transfer in Reinforcement Learning with Discrete Markov Decision Processes
by: Vora, Kevin, et al.
Published: (2025)

MATE: Solving Contextual Markov Decision Processes with Memory of Accumulated Transition Embeddings
by: Hwang, Himchan, et al.
Published: (2026)

REValueD: Regularised Ensemble Value-Decomposition for Factorisable Markov Decision Processes
by: Ireland, David, et al.
Published: (2024)

Globally Optimal Hierarchical Reinforcement Learning for Linearly-Solvable Markov Decision Processes
by: Infante, Guillermo, et al.
Published: (2021)

Conformal Off-Policy Evaluation in Markov Decision Processes
by: Foffano, Daniele, et al.
Published: (2023)

Reinforcement Learning in Switching Non-Stationary Markov Decision Processes: Algorithms and Convergence Analysis
by: Amiri, Mohsen, et al.
Published: (2025)

Policy Gradient Algorithms with Monte Carlo Tree Learning for Non-Markov Decision Processes
by: Morimura, Tetsuro, et al.
Published: (2022)

Quantum Speedups in Regret Analysis of Infinite Horizon Average-Reward Markov Decision Processes
by: Ganguly, Bhargav, 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)

Regret Analysis of Policy Gradient Algorithm for Infinite Horizon Average Reward Markov Decision Processes
by: Bai, Qinbo, et al.
Published: (2023)

Improved Sample Complexity Analysis of Natural Policy Gradient Algorithm with General Parameterization for Infinite Horizon Discounted Reward Markov Decision Processes
by: Mondal, Washim Uddin, et al.
Published: (2023)

Observation Adaptation via Annealed Importance Resampling for Partially Observable Markov Decision Processes
by: Zhang, Yunuo, et al.
Published: (2025)

An Information Theoretic Evaluation Metric For Strong Unlearning
by: Jeon, Dongjae, et al.
Published: (2024)

Burning RED: Unlocking Subtask-Driven Reinforcement Learning and Risk-Awareness in Average-Reward Markov Decision Processes
by: Rojas, Juan Sebastian, et al.
Published: (2024)

An Offline Risk-aware Policy Selection Method for Bayesian Markov Decision Processes
by: Angelotti, Giorgio, et al.
Published: (2021)

Generalized Similarity U: A Non-parametric Test of Association Based on Similarity
by: Wei, Changshuai, et al.
Published: (2018)