loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Authors: Volkan Ustun 1 ; Ronit Jorvekar 2 ; Nikolos Gurney 1 ; David Pynadath 1 ; 2 and Yunzhe Wang 3

Affiliations: 1 Institute for Creative Technologies, University of Southern California, Playa Vista, CA, U.S.A. ; 2 Department of Computer Science, University of Southern California, Los Angeles, CA, U.S.A. ; 3 Department of Computer Science, Columbia University, New York, NY, U.S.A.

Keyword(s): Artificial Social Intelligence, Graph Neural Networks, Route Planning, Urban Search and Rescue.

Abstract: In the context of Urban Search and Rescue (USAR) missions, efficient routing performance is of paramount importance for the success of a USAR team. Artificial Social Intelligence (ASI) agents could play a crucial role in guiding and interacting with these teams, and an analysis of the routing choices made by USAR teams can offer valuable insights into their overall performance and provide guidance for interventions by ASI agents. This study capitalizes on recent advancements in Graph Neural Networks, transformers, and attention models to harness their capabilities as neural heuristics for rapidly generating near-optimal routes in routing challenges. Specifically, we propose a real-time decision framework to scrutinize and evaluate routing decisions executed by participants during the DARPA ASIST Minecraft USAR Task. This assessment involves comparing the routing decisions made by participants and routes concurrently generated and recommended by neural heuristics employing Graph Neura l Networks with attention mechanisms. Furthermore, our investigation delves into the potential of routing decision assessments as informative indicators for an ASI agent, aiding in identifying scenarios necessitating intervention. This research contributes to using quantitative metrics, such as routing efficiency, as meaningful signals for ASI agents to monitor the performance of USAR teams through integrating state-of-the-art AI techniques. Ultimately, this integration could enhance the efficiency and effectiveness of an ASI in guiding search and rescue operations. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.118.1.25

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Ustun, V.; Jorvekar, R.; Gurney, N.; Pynadath, D. and Wang, Y. (2024). Assessing Routing Decisions of Search and Rescue Teams in Service of an Artificial Social Intelligence Agent. In Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART; ISBN 978-989-758-680-4; ISSN 2184-433X, SciTePress, pages 313-320. DOI: 10.5220/0012388100003636

@conference{icaart24,
author={Volkan Ustun. and Ronit Jorvekar. and Nikolos Gurney. and David Pynadath. and Yunzhe Wang.},
title={Assessing Routing Decisions of Search and Rescue Teams in Service of an Artificial Social Intelligence Agent},
booktitle={Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},
year={2024},
pages={313-320},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012388100003636},
isbn={978-989-758-680-4},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART
TI - Assessing Routing Decisions of Search and Rescue Teams in Service of an Artificial Social Intelligence Agent
SN - 978-989-758-680-4
IS - 2184-433X
AU - Ustun, V.
AU - Jorvekar, R.
AU - Gurney, N.
AU - Pynadath, D.
AU - Wang, Y.
PY - 2024
SP - 313
EP - 320
DO - 10.5220/0012388100003636
PB - SciTePress