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We present a framework that incorporates the idea of bounded rationality into dynamic stochastic pursuit-evasion games. The solution of a stochastic game is characterized, in general, by its (Nash) equilibria in feedback form. However,…

Systems and Control · Electrical Eng. & Systems 2020-03-17 Yue Guan , Dipankar Maity , Christopher M. Kroninger , Panagiotis Tsiotras

This work considers two-player zero-sum semi-Markov games with incomplete information on one side and perfect observation. At the beginning, the system selects a game type according to a given probability distribution and informs to Player…

Optimization and Control · Mathematics 2021-07-16 Fang Chen , Xianping Guo , Zhong-Wei Liao

In this paper, we consider a partial observed two-person zero-sum stochastic differential game problem where the system is governed by a stochastic differential equation of mean-field type. Under standard assumptions on the coefficients,…

Optimization and Control · Mathematics 2016-11-15 Maoning Tang , Qingxin Meng

Information gathering while interacting with other agents under sensing and motion uncertainty is critical in domains such as driving, service robots, racing, or surveillance. The interests of agents may be at odds with others, resulting in…

Robotics · Computer Science 2021-05-14 Wilko Schwarting , Alyssa Pierson , Sertac Karaman , Daniela Rus

The connection between game theory, convex optimization, and geometry is deep. There are many applications of linear programming methods and polyhedral representation conversion methods in game theory. In this paper, we discuss two more…

Computer Science and Game Theory · Computer Science 2025-09-03 Zhuoer Zhang , Bryce Morsky

Modeling the purposeful behavior of imperfect agents from a small number of observations is a challenging task. When restricted to the single-agent decision-theoretic setting, inverse optimal control techniques assume that observed behavior…

Computer Science and Game Theory · Computer Science 2013-08-19 Kevin Waugh , Brian D. Ziebart , J. Andrew Bagnell

Partially observable Markov decision processes (POMDPs) provide an elegant mathematical framework for modeling complex decision and planning problems in stochastic domains in which states of the system are observable only indirectly, via a…

Artificial Intelligence · Computer Science 2011-06-02 M. Hauskrecht

The concept of leader--follower (or Stackelberg) equilibrium plays a central role in a number of real--world applications of game theory. While the case with a single follower has been thoroughly investigated, results with multiple…

Computer Science and Game Theory · Computer Science 2017-07-10 Nicola Basilico , Stefano Coniglio , Nicola Gatti

Computing worst-case robust strategies in pursuit-evasion games (PEGs) is time-consuming, especially when real-world factors like partial observability are considered. While important for general security purposes, real-time applicable…

Machine Learning · Computer Science 2026-05-15 Runyu Lu , Ruochuan Shi , Yuanheng Zhu , Dongbin Zhao

Multi-agent systems are prevalent in a wide range of domains including power systems, vehicular networks, and robotics. Two important problems to solve in these types of systems are how the intentions of non-coordinating agents can be…

Multiagent Systems · Computer Science 2025-09-30 Benjamin Alcorn , Eman Hammad

We introduce Boolean Observation Games, a subclass of multi-player finite strategic games with incomplete information and qualitative objectives. In Boolean observation games, each player is associated with a finite set of propositional…

Computer Science and Game Theory · Computer Science 2024-02-09 Hans van Ditmarsch , Sunil Simon

Game-theoretic inverse learning is the problem of inferring a player's objectives from their actions. We formulate an inverse learning problem in a Stackelberg game between a leader and a follower, where each player's action is the…

Computer Science and Game Theory · Computer Science 2024-10-15 William Ward , Yue Yu , Jacob Levy , Negar Mehr , David Fridovich-Keil , Ufuk Topcu

Searching the space of policies directly for the optimal policy has been one popular method for solving partially observable reinforcement learning problems. Typically, with each change of the target policy, its value is estimated from the…

Artificial Intelligence · Computer Science 2007-05-23 Leonid Peshkin , Christian R. Shelton

In many settings of interest, a policy is set by one party, the leader, in order to influence the action of another party, the follower, where the follower's response is determined by some private information. A natural question to ask is,…

Computer Science and Game Theory · Computer Science 2025-04-23 Michael Albert , Quinlan Dawkins , Minbiao Han , Haifeng Xu

We study the problem of online learning in Stackelberg games with side information between a leader and a sequence of followers. In every round the leader observes contextual information and commits to a mixed strategy, after which the…

Machine Learning · Computer Science 2026-05-05 Maria-Florina Balcan , Martino Bernasconi , Matteo Castiglioni , Andrea Celli , Keegan Harris , Zhiwei Steven Wu

In this paper, we study the leader-following consensus problem of multiple Euler-Lagrange systems subject to an uncertain leader system. We first establish an adaptive distributed observer for a neutrally stable linear leader system whose…

Systems and Control · Electrical Eng. & Systems 2019-09-18 Shimin Wang , Jie Huang

This paper investigates a robust incentive Stackelberg stochastic differential game problem for a linear-quadratic mean field system, where the model uncertainty appears in the drift term of the leader's state equation. Moreover, both the…

Optimization and Control · Mathematics 2026-03-31 Na Xiang , Jingtao Shi

Leadership games provide a powerful paradigm to model many real-world settings. Most literature focuses on games with a single follower who acts optimistically, breaking ties in favour of the leader. Unfortunately, for real-world…

Artificial Intelligence · Computer Science 2018-08-01 Giuseppe De Nittis , Alberto Marchesi , Nicola Gatti

In bilevel optimization problems, a leader and a follower make their decisions in a hierarchy, and both decisions may influence each other. Usually one assumes that both players have full knowledge also of the other player's data. In a more…

Optimization and Control · Mathematics 2026-02-19 Dorothee Henke

We consider an n-player symmetric stochastic game with weak interaction between the players. Time is continuous and the horizon and the number of states are finite. We show that the value function of each of the players can be approximated…

Analysis of PDEs · Mathematics 2018-07-13 Erhan Bayraktar , Asaf Cohen