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相关论文: On the Adversarial Convex Body Chasing Problem

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Corrigibility of autonomous agents is an under explored part of system design, with previous work focusing on single agent systems. It has been suggested that uncertainty over the human preferences acts to keep the agents corrigible, even…

计算机科学与博弈论 · 计算机科学 2025-01-10 Edmund Dable-Heath , Boyko Vodenicharski , James Bishop

The paper considers the problem of a leader that seeks to optimally influence the opinions of agents in a directed network through connecting with a limited number of the agents ("direct followers"), possibly in the presence of a fixed…

最优化与控制 · 数学 2018-06-20 Van Sy Mai , Eyad H. Abed

We put forward a new model of congestion games where agents have uncertainty over the routes used by other agents. We take a non-probabilistic approach, assuming that each agent knows that the number of agents using an edge is within a…

计算机科学与博弈论 · 计算机科学 2017-03-28 Reshef Meir , David Parkes

Extensive-form games are a common model for multiagent interactions with imperfect information. In two-player zero-sum games, the typical solution concept is a Nash equilibrium over the unconstrained strategy set for each player. In many…

计算机科学与博弈论 · 计算机科学 2019-02-07 Trevor Davis , Kevin Waugh , Michael Bowling

This paper fully studies distributed optimal consensus problem in non-directed dynamical networks. We consider a group of networked agents that are supposed to rendezvous at the optimal point of a collective convex objective function. Each…

最优化与控制 · 数学 2017-12-22 Amir Adibzadeh , Amir A. Suratgar , Mohammad B. Menhaja , Mohsen Zamani

We revisit Blackwell's celebrated approachability problem which considers a repeated vector-valued game between a player and an adversary. Motivated by settings in which the action set of the player or adversary (or both) is difficult to…

最优化与控制 · 数学 2025-06-17 Dan Garber , Mhna Massalha

The generation of feasible adversarial examples is necessary for properly assessing models that work in constrained feature space. However, it remains a challenging task to enforce constraints into attacks that were designed for computer…

人工智能 · 计算机科学 2022-05-04 Thibault Simonetto , Salijona Dyrmishi , Salah Ghamizi , Maxime Cordy , Yves Le Traon

This paper studies a 3D multiplayer reach-avoid differential game with a goal region and a play region. Multiple pursuers defend the goal region by consecutively capturing multiple evaders in the play region. The players have heterogeneous…

最优化与控制 · 数学 2020-02-17 Rui Yan , Xiaoming Duan , Zongying Shi , Yisheng Zhong , Francesco Bullo

This paper investigates a partial-information pursuit evasion game in which the Pursuer has a limited-range sensor to detect the Evader. Given a fixed final time, we derive the optimal evasion strategy for the Evader to maximize its…

计算机科学与博弈论 · 计算机科学 2024-01-24 Dipankar Maity , Alexander Von Moll , Daigo Shishika , Michael Dorothy

We introduce a problem in which a service vehicle seeks to guard a deadline (boundary) from dynamically arriving mobile targets. The environment is a rectangle and the deadline is one of its edges. Targets arrive continuously over time on…

机器人学 · 计算机科学 2016-11-17 Stephen L. Smith , Shaunak D. Bopardikar , Francesco Bullo

We study two-player multi-weighted reachability games played on a finite directed graph, where an agent, called P1, has several quantitative reachability objectives that he wants to optimize against an antagonistic environment, called P2.…

计算机科学与博弈论 · 计算机科学 2025-09-08 Thomas Brihaye , Aline Goeminne

We address the problem of persistent monitoring, where a finite set of mobile agents has to persistently visit a finite set of targets. Each of these targets has an internal state that evolves with linear stochastic dynamics. The agents can…

系统与控制 · 电气工程与系统科学 2020-04-23 Samuel C. Pinto , Sean B. Andersson , Julien M. Hendrickx , Christos G. Cassandras

Reinforcement learning is commonly concerned with problems of maximizing accumulated rewards in Markov decision processes. Oftentimes, a certain goal state or a subset of the state space attain maximal reward. In such a case, the…

人工智能 · 计算机科学 2024-08-23 Pavel Osinenko , Grigory Yaremenko , Georgiy Malaniya , Anton Bolychev , Alexander Gepperth

Constrained reinforcement learning has achieved promising progress in safety-critical fields where both rewards and constraints are considered. However, constrained reinforcement learning methods face challenges in striking the right…

机器学习 · 计算机科学 2024-10-29 Jianmina Ma , Jingtian Ji , Yue Gao

We consider a perimeter defense problem in a planar conical environment in which a single vehicle, having a finite capture radius, aims to defend a concentric perimeter from mobile intruders. The intruders are arbitrarily released at the…

数据结构与算法 · 计算机科学 2022-03-31 Shivam Bajaj , Eric Torng , Shaunak D. Bopardikar , Alexander Von Moll , Isaac Weintraub , Eloy Garcia , David W. Casbeer

Suppose a Bayesian agent seeks to traverse a graph. Each time she crosses an edge, she pays a price. The first time she reaches a node, there is a payoff. She has an opponent who can reduce the payoffs. This paper uses adversarial risk…

最优化与控制 · 数学 2026-02-12 David Banks , Elvan Ceyhan , Leah Johnson , Li Zhou

In this paper, a time-varying distributed convex optimization problem is studied for continuous-time multi-agent systems. Control algorithms are designed for the cases of single-integrator and double-integrator dynamics. Two discontinuous…

最优化与控制 · 数学 2016-09-07 Salar Rahili , Wei Ren

In this paper we investigate a differential game in which countably many dynamical objects pursue a single one. All the players perform simple motions. The duration of the game is fixed. The controls of a group of pursuers are subject to…

最优化与控制 · 数学 2014-10-10 Mehdi Salimi , Gafurjan Ibragimov , Stefan Siegmund , Somayeh Sharifi

We consider the problem of influence maximization in fixed networks for contagion models in an adversarial setting. The goal is to select an optimal set of nodes to seed the influence process, such that the number of influenced nodes at the…

社会与信息网络 · 计算机科学 2019-01-23 Justin Khim , Varun Jog , Po-Ling Loh

Adversarial machine learning, i.e., increasing the robustness of machine learning algorithms against so-called adversarial examples, is now an established field. Yet, newly proposed methods are evaluated and compared under unrealistic…

机器学习 · 计算机科学 2021-09-28 Maximilian Samsinger , Florian Merkle , Pascal Schöttle , Tomas Pevny