Zero--Sum Differential Game

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5 papers in the last 28 days · 0.1% of indexed attention

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Period ending 2026-09-21

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Period ending 2026-09-07

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28 papers

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Social Laws for Multi-agent Coordination in Stochastic Environments
Sep 16, 2026Rolando Fernandez, Caleb Probine, Tyler Lee +5Multi-Agent Coordination Multi-Agent Systems
Information Design in Smooth Games
Sep 14, 2026Alex Smolin, Takuro YamashitaZero--Sum Differential Game Interaction Design
High-Probability Nash Regret for Decentralized Learning in Markov $α$ -Potential Games: Episodic and Fully Online Asynchronous Algorithms with Applications to Markov Congestion Games
Sep 14, 2026S. Rasoul EtesamiZero--Sum Differential Game Nash Equilibrium
Robust PAC Learning of Concurrent Stochastic Games
Sep 3, 2026Angel Y. He, David ParkerZero--Sum Differential Game Nash Equilibrium
Differential Games for Compositional Handling of Competing Control Tasks
Sep 1, 2026Joshua Shay KricheliZero--Sum Differential Game Linear Quadratic Regulator
Robust Safety Filtering for Input-Constrained Underactuated Linear Systems
Aug 11, 2026Muhamad Rausyan FikriSafety Filters Control Barrier Functions
Learning under Opponent Unawareness in Linear-Quadratic Stochastic Games
Aug 8, 2026Dantong Chu, Xuefeng Gao, Yufei ZhangZero--Sum Differential Game Nash Equilibrium
A Forward-Inverse Dynamic Game Framework for Enhanced Multi-Agent Trajectory Planning
Aug 3, 2026Tianle Liu, Youcheng Niu, Jing Zeng +2Zero--Sum Differential Game Multi-Agent Reinforcement Learning
Algorithms for Equilibria in Concurrent Stopping Games
Jul 27, 2026Léonard Brice, Thomas A. Henzinger, K. S. ThejaswiniNash Equilibrium Zero--Sum Differential Game
PAC Learning in Turn-Based Stochastic Games with Reachability Objectives: A Decentralized Private Approach via Expected Conditional Distance
Jul 16, 2026Ali Asadi, Krishnendu Chatterjee, Pavol KebisZero--Sum Differential Game Reachability
Multi-Agent LLMs Fail to Explore Each Other
Jul 13, 2026Hyeong Kyu Choi, Jiatong Li, Wendi Li +2Diversity Zero--Sum Differential Game
Entropy-Regularized Reinforcement Learning for Linear-Quadratic Stackelberg Differential Games in Regime-Switching Diffusion Models
Jun 27, 2026Congde Hu, Danping Li, Lin Xu +1Entropy Regularized Reinforcement Learning Zero--Sum Differential Game
Entropy Regularized Reinforcement Learning for Zero-Sum Stochastic Differential Games in a Regime-Switching Jump-Diffusion Process
Jun 27, 2026Congde Hu, Zhuo Jin, Danping Li +1Zero--Sum Differential Game Stochastic Optimal Control
A Fast Convergent Algorithm for Solving Non-convex Partially-Decoupled Generalized Nash Equilibrium Problems
Jun 26, 2026Bennet Outland, Vishala AryaZero--Sum Differential Game Nash Equilibrium
Neural Parameter Calibration for Finite-State Mean Field Games
Jun 22, 2026Anna C. M. Thöni, Grégoire Lambrecht, Gökçe Dayanıklı +3Mean-Field Limit Zero--Sum Differential Game
Stationary Robust Mean-Field Games under Model Mismatches
Jun 21, 2026Yue WangMulti-Agent Reinforcement Learning Zero--Sum Differential Game
Mobile Target Search with Imperfect Perception: A Partially Observable Stochastic Game Theoretical Approach
Jun 18, 2026Hanzheng Zhang, Shu Liang, Shuyu LiuZero--Sum Differential Game Partially Observable Markov Decision Process
A Surveillance Evasion Game with Continuous Sensor Redeployment via Bilevel Optimization
May 27, 2026Jaehyeok Kim, Kartik A. Pant, Joseph Kinerson +4Uncrewed Aerial Vehicles Optimal Sensor Placement
Hamilton--Jacobi Reachability for Spacecraft Collision Avoidance
May 19, 2026Larry Hui, Jordan Kam, William Su +1Hamilton-Jacobi Reachability Collision Avoidance
Counterfactual Reasoning for Causal Responsibility Attribution in Probabilistic Multi-Agent Systems
May 13, 2026Chunyan Mu, Muhammad NajibMulti-Agent Systems Zero--Sum Differential Game
DelAC: A Multi-agent Reinforcement Learning of Team-Symmetric Stochastic Games
May 11, 2026Duan-Shin Lee, Yu-Hsiu HungZero--Sum Differential Game Nash Equilibrium
Automated Approach for Solving Infinite-state Polynomial Reachability Games
May 11, 2026Krishnendu Chatterjee, Ehsan Kafshdar Goharshady, Mehrdad Karrabi +2Reachability Zero--Sum Differential Game
Rethinking Priority Scheduling for Sequential Multi-Agent Decision Making in Stackelberg Games
May 8, 2026Xiangyu Liu, Liang Zhang, Bo Jin +1Zero--Sum Differential Game Multi-Agent Systems
A four-player potential game for barren-plateau-aware quantum ansatz design
Apr 23, 2026Rubén Darío GuerreroQuantum Circuit Simulation Quantum Approximate Optimization Algorithm
Policy Gradient with Self-Attention for Model-Free Distributed Nonlinear Multi-Agent Games
Sep 22, 2025Eduardo Sebastián, Maitrayee Keskar, Eeman Iqbal +3Multi-Agent Reinforcement Learning Zero--Sum Differential Game
Distributionally Robust Markov Games with Average Reward
Aug 5, 2025Zachary Roch, Yue WangZero--Sum Differential Game Markov Decision Processes
Captivity-Escape Games as a Means for Safety in Online Motion Generation
Jun 2, 2025Christopher Bohn, Manuel Hess, Sören HohmannSafety Constraints Escape
Decentralized Best-Response-Based Learning in Two-Player Zero-Sum Stochastic Games: A Finite-Sample Analysis
Sep 2, 2024Zaiwei Chen, Kaiqing Zhang, Eric Mazumdar +2Zero--Sum Differential Game Imperfect-Information Games

Sep 16, 2026 · cs.MAJ/K move · Enter open · S save

Social Laws for Multi-agent Coordination in Stochastic Environments

Rolando Fernandez, Caleb Probine, Tyler Lee, Jeffrey Chen+4

In multi-agent environments, coordinating agents to prevent interference and ensure robust individual performance is a critical challenge. Previous research on social laws for multi-agent systems has primarily focused on deterministic, goal-based settings. This paper extends the concept of social laws to stochastic, reward-based environments, proposing a formalism for defining and verifying their robustness under various conditions. We introduce the notion of

α

-robustness, a measure of the guaranteed utility each agent retains while pursuing its optimal single agent policy, assuming all agents obey the social law. We then present an approach for robustness verification of social laws in stochastic settings, based on a reduction to solving a series of Markov decision processes. Empirical evaluations on toy environments illustrate the potential of our framework.

Multi-Agent Coordination Multi-Agent Systems Zero--Sum Differential Game Multi-Robot Systems Optimal Policies Stochastic Environment

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