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We initiate the study of structured Stackelberg games, a novel form of strategic interaction between a leader and a follower where contextual information can be predictive of the follower's (unknown) type. Motivated by applications such as…

Computer Science and Game Theory · Computer Science 2026-05-18 Maria-Florina Balcan , Kiriaki Fragkia , Keegan Harris

Continuous games are multiplayer games in which strategy sets are compact and utility functions are continuous. These games typically have a highly complicated structure of Nash equilibria, and numerical methods for the equilibrium…

Computer Science and Game Theory · Computer Science 2022-07-12 T. Kroupa , T. Votroubek

This paper studies a system security problem in the context of observability based on a two-person noncooperative infinitely repeated game. Both the attacker and the defender have means to modify the dimension of the unobservable subspace,…

Optimization and Control · Mathematics 2025-06-11 Yueyue Xu , Panpan Zhou , Lin Wang , Zhixin Liu , Xiaoming Hu

This paper studies a stochastic robotic surveillance problem where a mobile robot moves randomly on a graph to capture a potential intruder that strategically attacks a location on the graph. The intruder is assumed to be omniscient: it…

Optimization and Control · Mathematics 2020-11-17 Xiaoming Duan , Dario Paccagnan , Francesco Bullo

Partially Observable Markov Games (POMGs) provide a general framework for modeling multi-agent sequential decision-making under asymmetric information. A common approach is to reformulate a POMG as a fully observable Markov game over belief…

Multiagent Systems · Computer Science 2026-04-08 Lan Sang , Chinmay Maheshwari

Batch reinforcement learning (RL) defines the task of learning from a fixed batch of data lacking exhaustive exploration. Worst-case optimality algorithms, which calibrate a value-function model class from logged experience and perform some…

Machine Learning · Statistics 2023-10-03 Wenzhuo Zhou , Annie Qu

We study a class of two-player zero-sum stochastic games known as \textit{blind stochastic games}, where players neither observe the state nor receive any information about it during the game. A central concept for analyzing long-duration…

Optimization and Control · Mathematics 2025-11-24 Krishnendu Chatterjee , David Lurie , Raimundo Saona , Bruno Ziliotto

Real world applications such as economics and policy making often involve solving multi-agent games with two unique features: (1) The agents are inherently asymmetric and partitioned into leaders and followers; (2) The agents have different…

Machine Learning · Computer Science 2021-11-04 Yu Bai , Chi Jin , Huan Wang , Caiming Xiong

Effective enforcement of laws and policies requires expending resources to prevent and detect offenders, as well as appropriate punishment schemes to deter violators. In particular, enforcement of privacy laws and policies in modern…

Computer Science and Game Theory · Computer Science 2013-03-06 Jeremiah Blocki , Nicolas Christin , Anupam Datta , Ariel D. Procaccia , Arunesh Sinha

Many non-trivial sequential decision-making problems are efficiently solved by relying on Bellman's optimality principle, i.e., exploiting the fact that sub-problems are nested recursively within the original problem. Here we show how it…

Artificial Intelligence · Computer Science 2022-11-16 Olivier Buffet , Jilles Dibangoye , Aurélien Delage , Abdallah Saffidine , Vincent Thomas

Mobile data offloading is an emerging technology to avoid congestion in cellular networks and improve the level of user satisfaction. In this paper, we develop a distributed market framework to price the offloading service, and conduct a…

Networking and Internet Architecture · Computer Science 2014-09-17 Kehao Wang , Francis C. M. Lau , Lin Chen , Robert Schober

This article studies linear-quadratic Stackelberg games between two dominating players (or equivalently, leaders) and a large group of followers, each of whom interacts under a mean field game (MFG) framework. Unlike the conventional…

Optimization and Control · Mathematics 2024-07-02 Dantong Chu , Kenneth Tsz Hin Ng , Sheung Chi Phillip Yam , Harry Zheng

We study an online learning problem in general-sum Stackelberg games, where players act in a decentralized and strategic manner. We study two settings depending on the type of information for the follower: (1) the limited information…

Machine Learning · Computer Science 2025-05-06 Yaolong Yu , Haipeng Chen

Stochastic games are an important class of problems that generalize Markov decision processes to game theoretic scenarios. We consider finite state two-player zero-sum stochastic games over an infinite time horizon with discounted rewards.…

Optimization and Control · Mathematics 2008-06-17 Parikshit Shah , Pablo A. Parrilo

This paper investigates leader-follower linear-quadratic stochastic graphon games, which consist of a single leader and a continuum of followers. The state equations of the followers interact through graphon coupling terms, with their…

Optimization and Control · Mathematics 2026-03-12 Weijia Chen , Jingtao Shi

This paper studies partially observable two-person zero-sum semi-Markov games under a probability criterion, in which the system state may not be completely observed. It focuses on the probability that the accumulated rewards of player 1…

Optimization and Control · Mathematics 2025-08-26 Xin Wen , Li Xia , Zhihui Yu

While Nash equilibrium has emerged as the central game-theoretic solution concept, many important games contain several Nash equilibria and we must determine how to select between them in order to create real strategic agents. Several Nash…

Computer Science and Game Theory · Computer Science 2024-04-30 Sam Ganzfried

In two-player finite-state stochastic games of partial observation on graphs, in every state of the graph, the players simultaneously choose an action, and their joint actions determine a probability distribution over the successor states.…

Computer Science and Game Theory · Computer Science 2011-07-13 Krishnendu Chatterjee , Laurent Doyen

This paper obtains the maximum principle for both stochastic (global) open-loop and stochastic (global) closed-loop Stackelberg differential games. For the closed-loop case, we use the theory of controlled forward-backward stochastic…

Optimization and Control · Mathematics 2012-10-30 Alain Bensoussan , Shaokuan Chen , Suresh P. Sethi

We present a linear--quadratic Stackelberg game with a large number of followers and we also derive the mean field limit of infinitely many followers. The relation between optimization and mean-field limit is studied and conditions for…

Optimization and Control · Mathematics 2020-11-09 Michael Herty , Sonja Steffensen , Anna Thünen