5 papers
Policy Stability for Measuring Operational Performance in Task Assignment with Time-Windows Under Internal Adversarial Influence
Roee M. Francos, Daniel Garces, Orhan Eren Akgün +1
We study autonomous pickup-and-delivery routing problems in which internal adversarial agents spoof their locations to attract request assignments and then intentionally leave thos…
Provably Stable Multi-Agent Routing with Bounded-Delay Adversaries in the Decision Loop
Roee M. Francos, Daniel Garces, Stephanie Gil
In this work, we are interested in studying multi-agent routing settings, where adversarial agents are part of the assignment and decision loop, degrading the performance of the fl…
Pro-Routing: Proactive Routing of Autonomous Multi-Capacity Robots for Pickup-and-Delivery Tasks
Daniel Garces, Stephanie Gil
We consider a multi-robot setting, where we have a fleet of multi-capacity autonomous robots that must service spatially distributed pickup-and-delivery requests with fixed maximum…
Data-Efficient Multi-Agent Spatial Planning with LLMs
Huangyuan Su, Aaron Walsman, Daniel Garces +2
In this project, our goal is to determine how to leverage the world-knowledge of pretrained large language models for efficient and robust learning in multiagent decision making. W…
Approximate Multiagent Reinforcement Learning for On-Demand Urban Mobility Problem on a Large Map (extended version)
Daniel Garces, Sushmita Bhattacharya, Dimitri Bertsekas +1
In this paper, we focus on the autonomous multiagent taxi routing problem for a large urban environment where the location and number of future ride requests are unknown a-priori,…