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Optimal escape Interdiction on transportation networks

Optimal escape Interdiction on transportation networks
Optimal escape Interdiction on transportation networks
Preventing crimes or terrorist attacks in urban areas is challenging. Law enforcement officers need to respond quickly to catch the attacker on his escape route, which is subject to time-dependent traffic conditions on transportation networks. The attacker can strategically choose his escape path and driving speed to avoid being captured. Existing work on security resource allocation has not considered such scenarios with time-dependent strategies for both players. Therefore, in this paper, we study the problem of efficiently scheduling security resources for interdicting the escaping attacker. We propose: 1) a new defender-attacker security game model for escape interdiction on transportation networks; and 2) an efficient double oracle algorithm to compute the optimal defender strategy, which combines mixed-integer linear programming formulations for best response problems and effective approximation algorithms for improving the scalability of the algorithms. Experimental evaluation shows that our approach significantly outperforms baselines in solution quality and scales up to realistic-sized transportation networks with hundreds of intersections.
Zhang, Youzhi
c5a29f2c-a55e-4cca-9fb2-2ff168050dfd
An, Bo
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Tran-Thanh, Long
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Wang, Zhen
964f3b2e-0c55-4cf4-add6-6fc7afb8fbdd
Gan, Jiarui
eaa9f4a0-ced7-48e9-b03e-ee10f21b76dc
Jennings, Nicholas R.
3f6b53c2-4b6d-4b9d-bb51-774898f6f136
Zhang, Youzhi
c5a29f2c-a55e-4cca-9fb2-2ff168050dfd
An, Bo
4b0743f9-91c9-4452-868c-1d12b4e9f456
Tran-Thanh, Long
e0666669-d34b-460e-950d-e8b139fab16c
Wang, Zhen
964f3b2e-0c55-4cf4-add6-6fc7afb8fbdd
Gan, Jiarui
eaa9f4a0-ced7-48e9-b03e-ee10f21b76dc
Jennings, Nicholas R.
3f6b53c2-4b6d-4b9d-bb51-774898f6f136

Zhang, Youzhi, An, Bo, Tran-Thanh, Long, Wang, Zhen, Gan, Jiarui and Jennings, Nicholas R. (2017) Optimal escape Interdiction on transportation networks. International Joint Conference on Artificial Intelligence, Melbourne, Australia. 19 - 25 Aug 2017. 9 pp .

Record type: Conference or Workshop Item (Paper)

Abstract

Preventing crimes or terrorist attacks in urban areas is challenging. Law enforcement officers need to respond quickly to catch the attacker on his escape route, which is subject to time-dependent traffic conditions on transportation networks. The attacker can strategically choose his escape path and driving speed to avoid being captured. Existing work on security resource allocation has not considered such scenarios with time-dependent strategies for both players. Therefore, in this paper, we study the problem of efficiently scheduling security resources for interdicting the escaping attacker. We propose: 1) a new defender-attacker security game model for escape interdiction on transportation networks; and 2) an efficient double oracle algorithm to compute the optimal defender strategy, which combines mixed-integer linear programming formulations for best response problems and effective approximation algorithms for improving the scalability of the algorithms. Experimental evaluation shows that our approach significantly outperforms baselines in solution quality and scales up to realistic-sized transportation networks with hundreds of intersections.

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EscapeInterdictionGameIJCAI2017_#2181 - Accepted Manuscript
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More information

Accepted/In Press date: 23 April 2017
Published date: August 2017
Venue - Dates: International Joint Conference on Artificial Intelligence, Melbourne, Australia, 2017-08-19 - 2017-08-25
Organisations: Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 411980
URI: https://eprints.soton.ac.uk/id/eprint/411980
PURE UUID: 1aba159b-162c-4a21-85b8-c76446461049
ORCID for Long Tran-Thanh: ORCID iD orcid.org/0000-0003-1617-8316

Catalogue record

Date deposited: 04 Jul 2017 16:31
Last modified: 14 Mar 2019 05:47

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Contributors

Author: Youzhi Zhang
Author: Bo An
Author: Long Tran-Thanh ORCID iD
Author: Zhen Wang
Author: Jiarui Gan
Author: Nicholas R. Jennings

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