The University of Southampton
University of Southampton Institutional Repository

HAC-ER: disaster response system based on human-agent collectives

HAC-ER: disaster response system based on human-agent collectives
HAC-ER: disaster response system based on human-agent collectives
This paper proposes a novel disaster management system called HAC-ER that addresses some of the challenges faced by emergency responders by enabling humans and agents, using state-of-the-art algorithms, to collaboratively plan and carry out tasks in teams referred to as human-agent collectives. In particular, HACER utilises crowdsourcing combined with machine learning to extract situational awareness information from large streams of reports posted by members of the public and trusted organisations. We then show how this information can inform human-agent teams in coordinating multi-UAV deployments as well as task planning for responders on the ground. Finally, HAC-ER incorporates a tool for tracking and analysing the provenance of information shared across the entire system. In summary, this paper describes a prototype system, validated by real-world emergency responders, that combines several state-of-the-art techniques for integrating humans and agents, and illustrates, for the first time, how such an approach can enable more effective disaster response operations.
533-541
Ramchurn, Sarvapali
1d62ae2a-a498-444e-912d-a6082d3aaea3
Simpson, Edwin
ebf1cc2d-6633-4182-ab5a-91c832816a97
Fischer, Joel
a320ad79-0fb5-464b-9eac-f74918b5ea68
Huynh, Trung Dong
ddea6cf3-5a82-4c99-8883-7c31cf22dd36
Ikuno, Yuki
2d92d5e3-3377-44fb-b573-5b140be71a8b
Reece, Steven
b79cac5b-bbd2-4038-b47d-3d4c845802aa
Jiang, Wenchao
c93f05be-0fe0-4f1f-b8d6-326001d8edb0
Wu, Feng
b79f9800-2819-40c8-96e7-3ad85f866f5e
Flann, Jack
e7c45bef-2d6b-410f-a7ab-4629f34fa086
Roberts, S.J.
d4ee9d51-aa0b-4385-92a0-68d9e2d895ae
Moreau, Luc
033c63dd-3fe9-4040-849f-dfccbe0406f8
Rodden, T.
98078833-9f01-4db0-9a29-702a0109b179
Jennings, N.R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Ramchurn, Sarvapali
1d62ae2a-a498-444e-912d-a6082d3aaea3
Simpson, Edwin
ebf1cc2d-6633-4182-ab5a-91c832816a97
Fischer, Joel
a320ad79-0fb5-464b-9eac-f74918b5ea68
Huynh, Trung Dong
ddea6cf3-5a82-4c99-8883-7c31cf22dd36
Ikuno, Yuki
2d92d5e3-3377-44fb-b573-5b140be71a8b
Reece, Steven
b79cac5b-bbd2-4038-b47d-3d4c845802aa
Jiang, Wenchao
c93f05be-0fe0-4f1f-b8d6-326001d8edb0
Wu, Feng
b79f9800-2819-40c8-96e7-3ad85f866f5e
Flann, Jack
e7c45bef-2d6b-410f-a7ab-4629f34fa086
Roberts, S.J.
d4ee9d51-aa0b-4385-92a0-68d9e2d895ae
Moreau, Luc
033c63dd-3fe9-4040-849f-dfccbe0406f8
Rodden, T.
98078833-9f01-4db0-9a29-702a0109b179
Jennings, N.R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30

Ramchurn, Sarvapali, Simpson, Edwin, Fischer, Joel, Huynh, Trung Dong, Ikuno, Yuki, Reece, Steven, Jiang, Wenchao, Wu, Feng, Flann, Jack, Roberts, S.J., Moreau, Luc, Rodden, T. and Jennings, N.R. (2015) HAC-ER: disaster response system based on human-agent collectives. At 14th International Conference on Autonomous Agents and Multi-Agent Systems 14th International Conference on Autonomous Agents and Multi-Agent Systems, Istanbul, Turkey. 04 - 08 May 2015. pp. 533-541.

Record type: Conference or Workshop Item (Paper)

Abstract

This paper proposes a novel disaster management system called HAC-ER that addresses some of the challenges faced by emergency responders by enabling humans and agents, using state-of-the-art algorithms, to collaboratively plan and carry out tasks in teams referred to as human-agent collectives. In particular, HACER utilises crowdsourcing combined with machine learning to extract situational awareness information from large streams of reports posted by members of the public and trusted organisations. We then show how this information can inform human-agent teams in coordinating multi-UAV deployments as well as task planning for responders on the ground. Finally, HAC-ER incorporates a tool for tracking and analysing the provenance of information shared across the entire system. In summary, this paper describes a prototype system, validated by real-world emergency responders, that combines several state-of-the-art techniques for integrating humans and agents, and illustrates, for the first time, how such an approach can enable more effective disaster response operations.

PDF fp634-ramchurn.pdf - Accepted Manuscript
Download (5MB)

More information

Published date: 2015
Venue - Dates: 14th International Conference on Autonomous Agents and Multi-Agent Systems, Istanbul, Turkey, 2015-05-04 - 2015-05-08
Organisations: Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 374070
URI: https://eprints.soton.ac.uk/id/eprint/374070
PURE UUID: 06b6006d-6792-4c1a-9349-d4c8ea8d5554
ORCID for Sarvapali Ramchurn: ORCID iD orcid.org/0000-0001-9686-4302
ORCID for Trung Dong Huynh: ORCID iD orcid.org/0000-0003-4937-2473
ORCID for Luc Moreau: ORCID iD orcid.org/0000-0002-3494-120X

Catalogue record

Date deposited: 09 Feb 2015 15:07
Last modified: 06 Jun 2018 13:04

Export record

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of https://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×