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Multi-leader multi-follower games are a class of hierarchical games in which a collection of leaders compete in a Nash game constrained by the equilibrium conditions of another Nash game amongst the followers. The resulting equilibrium…

Optimization and Control · Mathematics 2014-08-27 Ankur A. Kulkarni , Uday V. Shanbhag

We consider a variant of pursuit-evasion games where a single defender is tasked to defend a static target from a sequence of periodically arriving intruders. The intruders' objective is to breach the boundary of a circular target without…

Optimization and Control · Mathematics 2023-03-13 Arman Pourghorban , Dipankar Maity

In multi-agent problems requiring a high degree of cooperation, success often depends on the ability of the agents to adapt to each other's behavior. A natural solution concept in such settings is the Stackelberg equilibrium, in which the…

Machine Learning · Computer Science 2024-06-14 Robert Loftin , Mustafa Mert Çelikok , Herke van Hoof , Samuel Kaski , Frans A. Oliehoek

Game theory provides the gold standard for analyzing adversarial engagements, offering strong optimality guarantees. However, these guarantees often become brittle when assumptions such as perfect information are violated. Reinforcement…

Machine Learning · Computer Science 2026-03-18 Goutam Das , Michael Dorothy , Kyle Volle , Daigo Shishika

Given a mapped environment, we formulate the problem of visually tracking and following an evader using a probabilistic framework. In this work, we consider a non-holonomic robot with a limited visibility depth sensor in an indoor…

Robotics · Computer Science 2019-04-23 Varun Chandra Jammula , Anshul Rai , Yezhou Yang

In this paper, the problem of finding a Nash equilibrium of a multi-player game is considered. The players are only aware of their own cost functions as well as the action space of all players. We develop a relatively fast algorithm within…

Systems and Control · Computer Science 2017-05-09 Farzad Salehisadaghiani , Lacra Pavel

Hamilton-Jacobi (HJ) Reachability offers a framework for generating safe value functions and policies in the face of adversarial disturbance, but is limited by the curse of dimensionality. Physics-informed deep learning is able to overcome…

Robotics · Computer Science 2025-10-22 Ryan Teoh , Sander Tonkens , William Sharpless , Aijia Yang , Zeyuan Feng , Somil Bansal , Sylvia Herbert

In this work, we extend the convex bodies chasing problem (CBC) to an adversarial setting, where an agent (the Player) is tasked with chasing a sequence of convex bodies generated adversarially by another agent (the Opponent). The Player…

Systems and Control · Electrical Eng. & Systems 2023-03-20 Yue Guan , Longxu Pan , Daigo Shishika , Panagiotis Tsiotras

The Iterated Prisoner's Dilemma has guided research on social dilemmas for decades. However, it distinguishes between only two atomic actions: cooperate and defect. In real-world prisoner's dilemmas, these choices are temporally extended…

Artificial Intelligence · Computer Science 2018-03-02 Weixun Wang , Jianye Hao , Yixi Wang , Matthew Taylor

We study a class of zero-sum games between a singular-controller and a stopper over finite-time horizon. The underlying process is a multi-dimensional (locally non-degenerate) controlled stochastic differential equation (SDE) evolving in an…

Optimization and Control · Mathematics 2023-10-31 Andrea Bovo , Tiziano De Angelis , Elena Issoglio

We study nondeterministic strategies in parity games with the aim of computing a most permissive winning strategy. Following earlier work, we measure permissiveness in terms of the average number/weight of transitions blocked by the…

Logic in Computer Science · Computer Science 2013-01-14 Patricia Bouyer , Nicolas Markey , Jörg Olschewski , Michael Ummels

This paper provides a decomposition technique for the purpose of simplifying the solution of certain zero-sum differential games. The games considered terminate when the state reaches a target, which can be expressed as the union of a…

Optimization and Control · Mathematics 2014-09-17 Adriano Festa , Richard Vinter

This paper studies the problem of defending (1D and 2D) boundaries against a large number of continuous attacks with a heterogeneous group of defenders. The defender team has perfect information of the attack events within some time (finite…

Robotics · Computer Science 2023-02-21 Si Wei Feng , Jingjin Yu

Recent successes of game-theoretic formulations in ML have caused a resurgence of research interest in differentiable games. Overwhelmingly, that research focuses on methods and upper bounds on their speed of convergence. In this work, we…

Machine Learning · Computer Science 2020-09-16 Adam Ibrahim , Waïss Azizian , Gauthier Gidel , Ioannis Mitliagkas

Here we consider a game theoretic model of multilevel selection in which individuals compete based on their payoff and groups also compete based on the average payoff of group members. Our focus is on multilevel social dilemmas: games in…

Populations and Evolution · Quantitative Biology 2019-12-10 Daniel B. Cooney

With a large number of sensors and control units in networked systems, distributed support vector machines (DSVMs) play a fundamental role in scalable and efficient multi-sensor classification and prediction tasks. However, DSVMs are…

Machine Learning · Statistics 2017-10-16 Rui Zhang , Quanyan Zhu

In this paper we study a class of matrix-valued linear-quadratic mean-field-type games for both the risk-neutral, risk-sensitive and robust cases. Non-cooperation, full cooperation and adversarial between teams are treated. We provide a…

Optimization and Control · Mathematics 2019-06-06 Julian Barreiro-Gomez , Tyrone E. Duncan , Hamidou Tembine

This paper studies a two-player game with a quantitative surveillance requirement on an adversarial target moving in a discrete state space and a secondary objective to maximize short-term visibility of the environment. We impose the…

Robotics · Computer Science 2019-11-19 Suda Bharadwaj , Louis Ly , Bo Wu , Richard Tsai , Ufuk Topcu

Pursuit-evasion is the problem of capturing mobile targets with one or more pursuers. We use deep reinforcement learning for pursuing an omni-directional target with multiple, homogeneous agents that are subject to unicycle kinematic…

Multiagent Systems · Computer Science 2021-08-10 Cristino de Souza , Rhys Newbury , Akansel Cosgun , Pedro Castillo , Boris Vidolov , Dana Kulic

Many autonomous agents, such as intelligent vehicles, are inherently required to interact with one another. Game theory provides a natural mathematical tool for robot motion planning in such interactive settings. However, tractable…

Robotics · Computer Science 2023-03-23 Xinjie Liu , Lasse Peters , Javier Alonso-Mora
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