Cover Image

Optimism as Risk-Seeking in Multi-Agent Reinforcement Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Runyu, Li, Na, Ozdaglar, Asuman, Shamma, Jeff, Zardini, Gioele
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Systems and Control Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Zeroth-Order Constrained Optimization from a Control Perspective via Feedback Linearization
by: Zhang, Runyu, et al.
Published: (2025)

Equilibrium Selection for Multi-agent Reinforcement Learning: A Unified Framework
by: Zhang, Runyu, et al.
Published: (2024)

Offline Reinforcement Learning via Linear-Programming with Error-Bound Induced Constraints
by: Ozdaglar, Asuman, et al.
Published: (2022)

Random-Subspace Sequential Quadratic Programming for Constrained Zeroth-Order Optimization
by: Zhang, Runyu, et al.
Published: (2026)

Compositional Online Learning for Multi-Objective System Co-Design
by: Alharbi, Meshal, et al.
Published: (2026)

Scalable spectral representations for multi-agent reinforcement learning in network MDPs
by: Ren, Zhaolin, et al.
Published: (2024)

Distributional Uncertainty and Adaptive Decision-Making in System Co-design
by: Huang, Yujun, et al.
Published: (2026)

Implementation-Based Incentive Design for Autonomous Mobility-on-Demand and Transit Systems
by: Li, Xinling, et al.
Published: (2026)

On Composable and Parametric Uncertainty in Systems Co-Design
by: Huang, Yujun, et al.
Published: (2025)

What Data Enables Optimal Decisions? An Exact Characterization for Linear Optimization
by: Bennouna, Omar, et al.
Published: (2025)

Constrained Optimization From a Control Perspective via Feedback Linearization
by: Zhang, Runyu, et al.
Published: (2025)

Soft Robust MDPs and Risk-Sensitive MDPs: Equivalence, Policy Gradient, and Sample Complexity
by: Zhang, Runyu, et al.
Published: (2023)

Scalable Co-Design via Linear Design Problems: Compositional Theory and Algorithms
by: Cai, Yubo, et al.
Published: (2026)

Structured Cooperative Multi-Agent Reinforcement Learning: a Bayesian Network Perspective
by: Syed, Shahbaz P Qadri, et al.
Published: (2025)

MPC-Inspired Reinforcement Learning for Verifiable Model-Free Control
by: Lu, Yiwen, et al.
Published: (2023)

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

The Sample Complexity of Online Reinforcement Learning: A Multi-model Perspective
by: Muehlebach, Michael, et al.
Published: (2025)

Optimization and Learning in Open Multi-Agent Systems
by: Deplano, Diego, et al.
Published: (2025)

Risk-Aware Safe Reinforcement Learning for Control of Stochastic Linear Systems
by: Esmaeili, Babak, et al.
Published: (2025)

Temporal-Aware Deep Reinforcement Learning for Energy Storage Bidding in Energy and Contingency Reserve Markets
by: Li, Jinhao, et al.
Published: (2024)

Finite-Sample Guarantees for Learning Dynamics in Zero-Sum Polymatrix Games
by: Faizal, Fathima Zarin, et al.
Published: (2024)

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

Resilient Constrained Reinforcement Learning
by: Ding, Dongsheng, et al.
Published: (2023)

Major-Minor Mean Field Multi-Agent Reinforcement Learning
by: Cui, Kai, et al.
Published: (2023)

On the Foundation of Distributionally Robust Reinforcement Learning
by: Wang, Shengbo, et al.
Published: (2023)

Wasserstein Distributionally Robust Nash Equilibrium Seeking with Heterogeneous Data: A Lagrangian Approach
by: Wang, Zifan, et al.
Published: (2025)

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

Community-based Multi-Agent Reinforcement Learning with Transfer and Active Exploration
by: Shi, Zhaoyang
Published: (2025)

Attentive Convolutional Deep Reinforcement Learning for Optimizing Solar-Storage Systems in Real-Time Electricity Markets
by: Li, Jinhao, et al.
Published: (2024)

Operator Models for Continuous-Time Offline Reinforcement Learning
by: Hoischen, Nicolas, et al.
Published: (2025)

Convergence and stability of Q-learning in Hierarchical Reinforcement Learning
by: Manenti, Massimiliano, et al.
Published: (2025)

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

Hierarchical Reinforcement Learning Framework for Stochastic Spaceflight Campaign Design
by: Takubo, Yuji, et al.
Published: (2021)

Distributed Thompson sampling under constrained communication
by: Zerefa, Saba, et al.
Published: (2024)

Sample Complexity of the Linear Quadratic Regulator: A Reinforcement Learning Lens
by: Moghaddam, Amirreza Neshaei, et al.
Published: (2024)

Online Reinforcement Learning in Markov Decision Process Using Linear Programming
by: Leon, Vincent, et al.
Published: (2023)

Reinforcement Learning-based Control via Y-wise Affine Neural Networks (YANNs)
by: Braniff, Austin, et al.
Published: (2025)

Improved Regret Bound for Safe Reinforcement Learning via Tighter Cost Pessimism and Reward Optimism
by: Yu, Kihyun, et al.
Published: (2024)

Semi-on-Demand Transit Feeders with Shared Autonomous Vehicles and Reinforcement-Learning-Based Zonal Dispatching Control
by: Ng, Max T. M., et al.
Published: (2025)

Precise Insulin Delivery for Artificial Pancreas: A Reinforcement Learning Optimized Adaptive Fuzzy Control Approach
by: Mameche, Omar, et al.
Published: (2025)