Cover Image

Can Optimal Transport Improve Federated Inverse Reinforcement Learning?

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Millard, David, Baheri, Ali
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Systems and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

The Synergy Between Optimal Transport Theory and Multi-Agent Reinforcement Learning
by: Baheri, Ali, et al.
Published: (2024)

Optimal Transport-Assisted Risk-Sensitive Q-Learning
by: Shahrooei, Zahra, et al.
Published: (2024)

Concurrent Learning of Policy and Unknown Safety Constraints in Reinforcement Learning
by: Yifru, Lunet, et al.
Published: (2024)

Hierarchical Upper Confidence Bounds for Constrained Online Learning
by: Baheri, Ali
Published: (2024)

Wasserstein Adaptive Value Estimation for Actor-Critic Reinforcement Learning
by: Baheri, Ali, et al.
Published: (2025)

Metriplectic Conditional Flow Matching for Dissipative Dynamics
by: Baheri, Ali, et al.
Published: (2025)

Wasserstein Barycenter Soft Actor-Critic
by: Shahrooei, Zahra, et al.
Published: (2025)

Density-Ratio Weighted Behavioral Cloning: Learning Control Policies from Corrupted Datasets
by: Pandian, Shriram Karpoora Sundara, et al.
Published: (2025)

Optimizing Falsification for Learning-Based Control Systems: A Multi-Fidelity Bayesian Approach
by: Shahrooei, Zahra, et al.
Published: (2024)

A Survey on Reinforcement Learning in Aviation Applications
by: Razzaghi, Pouria, et al.
Published: (2022)

Wasserstein-Barycenter Consensus for Cooperative Multi-Agent Reinforcement Learning
by: Baheri, Ali
Published: (2025)

Implicit Constraint-Aware Off-Policy Correction for Offline Reinforcement Learning
by: Baheri, Ali
Published: (2025)

Hierarchical Neuro-Symbolic Decision Transformer
by: Baheri, Ali, et al.
Published: (2025)

Offline Reinforcement Learning via Inverse Optimization
by: Dimanidis, Ioannis, et al.
Published: (2025)

Stability of the Monge Map in Semi-Dual Optimal Transport
by: Selitskiy, Anton, et al.
Published: (2026)

Optimal Transport-Guided Safety in Temporal Difference Reinforcement Learning
by: Shahrooei, Zahra, et al.
Published: (2025)

Offline Hierarchical Reinforcement Learning via Inverse Optimization
by: Schmidt, Carolin, et al.
Published: (2024)

Federated Distributional Reinforcement Learning with Distributional Critic Regularization
by: Millard, David, et al.
Published: (2026)

Inverse Delayed Reinforcement Learning
by: Zhan, Simon Sinong, et al.
Published: (2024)

Nonuniqueness and Convergence to Equivalent Solutions in Observer-based Inverse Reinforcement Learning
by: Town, Jared, et al.
Published: (2022)

Stable Inverse Reinforcement Learning: Policies from Control Lyapunov Landscapes
by: Tesfazgi, Samuel, et al.
Published: (2024)

Inverse Reinforcement Learning for Minimum-Exposure Paths in Spatiotemporally Varying Scalar Fields
by: Ballentine, Alexandra E., et al.
Published: (2025)

Provably Optimal Reinforcement Learning under Safety Filtering
by: Oh, Donggeon David, et al.
Published: (2025)

A Reinforcement Learning Approach for Optimal Control in Microgrids
by: Salaorni, Davide, et al.
Published: (2025)

Towards Fast Rates for Federated and Multi-Task Reinforcement Learning
by: Zhu, Feng, et al.
Published: (2024)

Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning
by: Zhang, Chenyu, et al.
Published: (2024)

Actively Learning Reinforcement Learning: A Stochastic Optimal Control Approach
by: Ramadan, Mohammad S., et al.
Published: (2023)

Asynchronous Federated Learning: A Scalable Approach for Decentralized Machine Learning
by: Forootani, Ali, et al.
Published: (2024)

The Ground Cost for Optimal Transport of Angular Velocity
by: Elamvazhuthi, Karthik, et al.
Published: (2025)

PEARL: Preconditioner Enhancement through Actor-critic Reinforcement Learning
by: Millard, David, et al.
Published: (2025)

Optimal Batch-Size Control for Low-Latency Federated Learning with Device Heterogeneity
by: Yang, Huiling, et al.
Published: (2025)

Enhancing Cyber Resilience of Networked Microgrids using Vertical Federated Reinforcement Learning
by: Mukherjee, Sayak, et al.
Published: (2022)

Deep Reinforcement Learning-driven Cross-Community Energy Interaction Optimal Scheduling
by: Li, Yang, et al.
Published: (2023)

Improving Stochastic Action-Constrained Reinforcement Learning via Truncated Distributions
by: Stolz, Roland, et al.
Published: (2025)

Can Transformers Learn Optimal Filtering for Unknown Systems?
by: Balim, Haldun, et al.
Published: (2023)

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning
by: Li, Jiayu, et al.
Published: (2025)

Topology-Aware Graph Reinforcement Learning for Energy Storage Systems Optimal Dispatch in Distribution Networks
by: Gao, Shuyi, et al.
Published: (2026)

Model-free Reinforcement Learning for Model-based Control: Towards Safe, Interpretable and Sample-efficient Agents
by: Banker, Thomas, et al.
Published: (2025)

Improving a Proportional Integral Controller with Reinforcement Learning on a Throttle Valve Benchmark
by: Daoudi, Paul, et al.
Published: (2024)

Data-Driven Density Steering via the Gromov-Wasserstein Optimal Transport Distance
by: Nakashima, Haruto, et al.
Published: (2025)