Adam Meyerson

University of California, Los Angeles, Carnegie Mellon University

Papers

Total Citations

589

H-Index

About

Adam Meyerson is a leading researcher in the intersection of algorithmic theory and multi-agent robotics, with a core focus on approximation algorithms, auction-based coordination, and routing optimization. His most influential work provides rigorous theoretical foundations for practical multi-robot systems. Meyerson’s seminal 2005 paper on “Auction-Based Multi-Robot Routing” (294 citations) bridges a critical gap by offering the first theoretical performance analysis of auction methods for robot coordination, moving beyond purely experimental validation. He further advanced the field with his 2004 paper on approximation algorithms for the orienteering and discounted-reward TSP (175 citations), introducing the first constant-factor approximation for these problems—a breakthrough with direct applications in robot navigation and prize-collecting routing. His 2006 work on “The Power of Sequential Single-Item Auctions for Agent Coordination” (120 citations) formalized how simple auction mechanisms can achieve robust, fault-tolerant team coordination. Collectively, Meyerson’s contributions have shaped both algorithmic theory and practical multi-agent systems, providing provable guarantees for problems that were previously only studied empirically. His work remains essential reading for researchers in robotics, operations research, and theoretical computer science.