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We study the design of a decentralized two-sided matching market in which agents' search is guided by the platform. There are finitely many agent types, each with (potentially random) preferences drawn from known type-specific…

Computer Science and Game Theory · Computer Science 2021-08-19 Nicole Immorlica , Brendan Lucier , Vahideh Manshadi , Alexander Wei

We introduce the study of search games between a mobile Searcher and an immobile Hider in a new setting in which the Searcher has some potentially erroneous information, i.e., a prediction on the Hider's position. The objective is to…

Computer Science and Game Theory · Computer Science 2024-09-05 Spyros Angelopoulos , Thomas Lidbetter , Konstantinos Panagiotou

In this work, we consider classification of agents who can both game and improve. For example, people wishing to get a loan may be able to take some actions that increase their perceived credit-worthiness and others that also increase their…

Computer Science and Game Theory · Computer Science 2022-03-02 Saba Ahmadi , Hedyeh Beyhaghi , Avrim Blum , Keziah Naggita

We consider the problem of finding a door along a wall with a blind robot that neither knows the distance to the door nor the direction towards of the door. This problem can be solved with the well-known doubling strategy yielding an…

Computational Geometry · Computer Science 2010-12-24 Tom Kamphans , Elmar Langetepe

This paper addresses a prevailing assumption in single-agent heuristic search theory- that problem-solving algorithms should guarantee shortest-path solutions, which are typically called optimal. Optimality implies a metric for judging…

Artificial Intelligence · Computer Science 2013-04-10 Othar Hansson , Andy Mayer

Multi-Agent Path Finding (MAPF) seeks collision-free paths for multiple agents from their respective starting locations to their respective goal locations while minimizing path costs. Although many MAPF algorithms were developed and can…

Multiagent Systems · Computer Science 2024-12-24 Shuai Zhou , Shizhe Zhao , Zhongqiang Ren

Autonomous agents powered by LLMs and Retrieval-Augmented Generation (RAG) are proficient consumers of digital content but remain unidirectional, a limitation we term epistemic asymmetry. This isolation leads to redundant reasoning and…

Artificial Intelligence · Computer Science 2025-12-25 Zan-Kai Chong , Hiroyuki Ohsaki , Bryan Ng

We study prioritized planning for Multi-Agent Path Finding (MAPF). Existing prioritized MAPF algorithms depend on rule-of-thumb heuristics and random assignment to determine a fixed total priority ordering of all agents a priori. We instead…

Artificial Intelligence · Computer Science 2018-12-18 Hang Ma , Daniel Harabor , Peter J. Stuckey , Jiaoyang Li , Sven Koenig

Consider the following classical search problem: given a target point $p\in \Re$, starting at the origin, find $p$ with minimum cost, where cost is defined as the distance travelled. Let $D$ be the distance of $p$ from the origin. When no…

Data Structures and Algorithms · Computer Science 2014-11-05 Prosenjit Bose , Jean-Lou De Carufel

We consider the problem of locating a single facility on the real line. This facility serves a set of agents, each of whom is located on the line, and incurs a cost equal to his distance from the facility. An agent's location is private…

Computer Science and Game Theory · Computer Science 2014-09-17 Itai Feigenbaum , Jay Sethuraman , Chun Ye

We consider the problem of exploring an unknown tree with a team of $k$ initially colocated mobile agents. Each agent has limited energy and cannot, as a result, traverse more than $B$ edges. The goal is to maximize the number of nodes…

Data Structures and Algorithms · Computer Science 2018-02-20 Evangelos Bampas , Jérémie Chalopin , Shantanu Das , Jan Hackfeld , Christina Karousatou

We address the problem of planning collision-free paths for multiple agents using optimization methods known as proximal algorithms. Recently this approach was explored in Bento et al. 2013, which demonstrated its ease of parallelization…

Robotics · Computer Science 2015-04-14 José Bento , Nate Derbinsky , Charles Mathy , Jonathan S. Yedidia

We study the problem of how to coordinate the actions of independent agents in a distributed system where message arrival times are unbounded, but are determined by an exponential probability distribution. Asynchronous protocols executed in…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-11-10 Ariel Livshits , Yoram Moses

In this paper, we investigate the problem of joint searching and tracking of multiple mobile targets by a group of mobile agents. The targets appear and disappear at random times inside a surveillance region and their positions are random…

Systems and Control · Electrical Eng. & Systems 2023-02-06 Savvas Papaioannou , Panayiotis Kolios , Theocharis Theocharides , Christos G. Panayiotou , Marios M. Polycarpou

Many real-life contractual relations differ completely from the clean, static model at the heart of principal-agent theory. Typically, they involve repeated strategic interactions of the principal and agent, taking place under uncertainty…

In multi-agent search planning for a randomly moving and camouflaging target, we examine heterogeneous searchers that differ in terms of their endurance level, travel speed, and detection ability. This leads to a convex mixed-integer…

Optimization and Control · Mathematics 2023-11-03 Miguel Lejeune , Johannes O. Royset , Wenbo Ma

We present a scalable and effective multi-agent safe motion planner that enables a group of agents to move to their desired locations while avoiding collisions with obstacles and other agents, with the presence of rich obstacles,…

Robotics · Computer Science 2020-12-17 Jingkai Chen , Jiaoyang Li , Chuchu Fan , Brian Williams

This paper addresses the problem of both actively searching and tracking multiple unknown dynamic objects in a known environment with multiple cooperative autonomous agents with partial observability. The tracking of a target ends when the…

We revisit multi-agent asynchronous online optimization with delays, where only one of the agents becomes active for making the decision at each round, and the corresponding feedback is received by all the agents after unknown delays.…

Machine Learning · Computer Science 2026-02-05 Lingchan Bao , Tong Wei , Yuanyu Wan

Consider the scenario where multiple agents have to move in an optimal way through a network, each one towards their ending position while avoiding collisions. By optimal, we mean as fast as possible, which is evaluated by a measure known…

Computational Complexity · Computer Science 2025-06-02 Foivos Fioravantes , Dušan Knop , Jan Matyáš Křišťan , Nikolaos Melissinos , Michal Opler