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We study the class of reach-avoid dynamic games in which multiple agents interact noncooperatively, and each wishes to satisfy a distinct target criterion while avoiding a failure criterion. Reach-avoid games are commonly used to express…

Systems and Control · Electrical Eng. & Systems 2022-03-03 Dennis R. Anthony , Duy P. Nguyen , David Fridovich-Keil , Jaime F. Fisac

Achieving the capability of adapting to ever-changing environments is a critical step towards building fully autonomous robots that operate safely in complicated scenarios. In multiagent competitive scenarios, agents may have to adapt to…

Machine Learning · Computer Science 2022-03-16 Macheng Shen , Jonathan P. How

This paper suveys different variants of the following problem: Given a convex set $K$ and a sequence $\{C_i\}$ of convex bodies in $E^n$, is it possible to pack the sequence of bodies in $K$ or cover $K$ with the bodies? Algorithmic…

Metric Geometry · Mathematics 2022-02-24 Gábor Fejes Tóth

This work investigates the challenge of ensuring safety guarantees in the presence of uncontrollable agents, whose behaviors are stochastic and depend on both their own and the system's states. We present a neural model predictive control…

Systems and Control · Electrical Eng. & Systems 2026-04-21 Shuqi Wang , Mingyang Feng , Yu Chen , Yue Gao , Xiang Yin

An ideal strategy in zero-sum games should not only grant the player an average reward no less than the value of Nash equilibrium, but also exploit the (adaptive) opponents when they are suboptimal. While most existing works in Markov games…

Machine Learning · Computer Science 2022-06-15 Qinghua Liu , Yuanhao Wang , Chi Jin

This paper studies the time-optimal path tracking problem for a team of cooperating robotic manipulators carrying an object. Considering the problem for rigidly grasped objects, we show that it can be cast as a convex optimization problem…

Robotics · Computer Science 2023-03-14 Hamed Haghshenas , Anders Hansson , Mikael Norrlöf

We study the safe reinforcement learning problem with nonlinear function approximation, where policy optimization is formulated as a constrained optimization problem with both the objective and the constraint being nonconvex functions. For…

Machine Learning · Computer Science 2019-10-29 Ming Yu , Zhuoran Yang , Mladen Kolar , Zhaoran Wang

Generating competitive strategies and performing continuous motion planning simultaneously in an adversarial setting is a challenging problem. In addition, understanding the intent of other agents is crucial to deploying autonomous systems…

Robotics · Computer Science 2025-06-17 Hongrui Zheng , Zhijun Zhuang , Stephanie Wu , Shuo Yang , Rahul Mangharam

We consider concurrent games played on graphs. At every round of a game, each player simultaneously and independently selects a move; the moves jointly determine the transition to a successor state. Two basic objectives are the safety…

Computer Science and Game Theory · Computer Science 2008-09-25 Krishnendu Chatterjee , Luca de Alfaro , Thomas A. Henzinger

The use of visual sensors is flourishing, driven among others by the several applications in detection and prevention of crimes or dangerous events. While the problem of optimal camera placement for total coverage has been solved for a…

Computational Geometry · Computer Science 2023-02-28 Gaia Carenini , Alexandre Duplessis

Separable convex optimization problems with linear ascending inequality and equality constraints are addressed in this paper. Under an ordering condition on the slopes of the functions at the origin, an algorithm that determines the optimum…

Information Theory · Computer Science 2011-07-22 Arun Padakandla , Rajesh Sundaresan

In this paper, the problem of reaching formation for a network of rigid agents over a special orthogonal group is investigated by considering bearing-only constraints as the desired formation. Each agent is able to gather the measurements…

Systems and Control · Electrical Eng. & Systems 2023-10-02 Sara Mansourinasab , Mahdi Sojoodi , Seyed Reza Moghadasi

Imitation is widely observed in populations of decision-making agents. Using our recent convergence results for asynchronous imitation dynamics on networks, we consider how such networks can be efficiently driven to a desired equilibrium…

Computer Science and Game Theory · Computer Science 2017-04-17 James Riehl , Pouria Ramazi , Ming Cao

When modeling robot interactions as Nash equilibrium problems, it is desirable to place coupled constraints which restrict these interactions to be safe and acceptable (for instance, to avoid collisions). Such games are continuous with…

Computer Science and Game Theory · Computer Science 2025-06-03 Mel Krusniak , Forrest Laine

This thesis presents some geometric insights into three different types of two player prediction games -- namely general learning task, prediction with expert advice, and online convex optimization. These games differ in the nature of the…

Machine Learning · Computer Science 2018-05-23 Parameswaran Kamalaruban

We introduce a class of learning problems where the agent is presented with a series of tasks. Intuitively, if there is relation among those tasks, then the information gained during execution of one task has value for the execution of…

Machine Learning · Computer Science 2012-09-06 Christos Dimitrakakis

We consider a stochastic convex optimization problem that requires minimizing a sum of misspecified agentspecific expectation-valued convex functions over the intersection of a collection of agent-specific convex sets. This misspecification…

Optimization and Control · Mathematics 2015-09-22 Aswin Kannan , Angelia Nedich , Uday V. Shanbhag

We consider multi-agent decision making where each agent optimizes its convex cost function subject to individual and coupling constraints. The constraint sets are compact convex subsets of a Euclidean space. To learn Nash equilibria, we…

Optimization and Control · Mathematics 2018-10-16 Tatiana Tatarenko , Maryam Kamgarpour

Suppose an escaping player ("human") moves continuously at maximum speed $1$ in the interior of a region, while a pursuing player ("zombie") moves continuously at maximum speed $r$ outside the region. For what $r$ can the first player…

Computational Geometry · Computer Science 2025-10-21 Zachary Abel , Hugo Akitaya , Erik D. Demaine , Martin L. Demaine , Adam Hesterberg , Jason S. Ku , Jayson Lynch

We explored the Patrol Security Game (PSG), a robotic patrolling problem modeled as an extensive-form Stackelberg game, where the attacker determines the timing, location, and duration of their attack. Our objective is to devise a…

Artificial Intelligence · Computer Science 2024-10-22 Hao-Tsung Yang , Ting-Kai Weng , Ting-Yu Chang , Kin Sum Liu , Shan Lin , Jie Gao , Shih-Yu Tsai