Work

Profiles, Proxies, and Assumptions: Decentralized, Communications-Resilient Planning, Allocation, and Scheduling

Year: 2019

Type: conference-paper

Abstract: Degraded communications are expected in large-scale disaster response and military operations, which nevertheless require rapid, concerted actions by distributed decision makers, each with limited visibility into the changing situation and in charge of a limited set of resources. We describe LAPLATA, a novel architecture that addresses these challenges by separating mission planning from allocation/scheduling for scalability but at the cost of some negotiation. We describe formal algorithms that achieve near-optimal performance according to mission completion percentage and subject matter expert review: assumption-based planning and replanning, profileassisted cooperative allocation, and schedule negotiation. We validate our approach on a realistic problem specification and compare results against subject matter expert solutions.

Source: Proceedings of the AAAI Conference on Artificial Intelligence

DOI: 10.1609/aaai.v33i01.33019504

Authors: Ugur Kuter, Brian Kettler, Katherine Guo, Martin Hofmann, Valerie Champagne, Kurt Lachevet, Jennifer Lautenschlager, Robert P. Goldman, Luis Asencios, Josh Hamell

Institutions: Smart Information Flow Technologies (United States), Lockheed Martin (United States), United States Air Force Research Laboratory

Language: English

Topic: AI-based Problem Solving and Planning

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

Funder: Air Force Research Laboratory

OpenAlex ID: W2966085774

FWCI:

Cites: 14

Cited by:

Related to: 10