poster

Strategic guard placement for optimal response toalarms in security games

Authors:

Nicola Basilico,

Nicola GattiAuthors Info & Claims

AAMAS '14: Proceedings of the 2014 international conference on Autonomous agents and multi-agent systems

Pages 1481 - 1482

Published: 05 May 2014 Publication History

Get Access

Abstract

We introduce a Security Game with a single static guard that is supported by a number of spatially imperfect alarms. We model this setting with two non-cooperative games modeling two different strategic interactions between a Defender and an Attacker. In the first one the Defender has to respond to an activated alarm given its current position (Alarm-Response Game). In the second one, the Defender has to determine the best static placement from which undertakes any alarm response (Guard-Placement Game).

References

[1]

N. Basilico, N. Gatti, and F. Amigoni. Patrolling security games: Definition and algorithms for solving large instances with single patroller and single intruder. ARTIF INTELL, 184--185:78--123, 2012.

Digital Library

Google Scholar

[2]

N. Basilico, N. Gatti, and F. Villa. Asynchronous multi-robot patrolling against intrusion in arbitrary topologies. In AAAI, pages 1224--1229, 2010.

Digital Library

Google Scholar

[3]

M. Jain, B. An, and M. Tambe. An overview of recent application trends at the AAMAS conference: Security, sustainability, and safety. AI Magazine, 33(3):14--28, 2012.

Crossref

Google Scholar

[4]

E. Munoz de Cote, R. Stranders, N. Basilico, N. Gatti, and N. Jennings. Introducing alarms in adversarial patrolling games. In AAMAS, pages 1275--1276, 2013.

Digital Library

Google Scholar

Cited By

View all

Gholami SYadav ATran-Thanh LDilkina BTambe MElkind EVeloso MAgmon NTaylor M(2019)Don't Put All Your Strategies in One BasketProceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems10.5555/3306127.3331719(395-403)Online publication date: 8-May-2019
https://dl.acm.org/doi/10.5555/3306127.3331719
Gholami SMc Carthy SDilkina BPlumptre ATambe MDriciru MWanyama FRwetsiba ANsubaga MMabonga JOkello TEnyel EAndre EKoenig SDastani MSukthankar G(2018)Adversary Models Account for Imperfect Crime DataProceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems10.5555/3237383.3237505(823-831)Online publication date: 9-Jul-2018
https://dl.acm.org/doi/10.5555/3237383.3237505
Kar DFord BGholami SFang FPlumptre ATambe MDriciru MWanyama FRwetsiba ANsubaga MMabonga JLarson KWinikoff MDas SDurfee E(2017)Cloudy with a Chance of PoachingProceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems10.5555/3091125.3091153(159-167)Online publication date: 8-May-2017
https://dl.acm.org/doi/10.5555/3091125.3091153
Show More Cited By

Index Terms

Strategic guard placement for optimal response toalarms in security games
1. Computing methodologies
  1. Artificial intelligence
    1. Distributed artificial intelligence
      1. Multi-agent systems

Recommendations

Hard and soft equilibria in boolean games
AAMAS '14: Proceedings of the 2014 international conference on Autonomous agents and multi-agent systems

A fundamental problem in game theory is the possibility of reaching equilibrium outcomes with undesirable properties, e.g., inefficiency. The economics literature abounds with models that attempt to modify games in order to eliminate such undesirable ...
Local search techniques for computing equilibria in two-player general-sum strategic-form games
AAMAS '10: Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1

The computation of a Nash equilibrium in a game is a challenging problem in artificial intelligence. This is because the computational time of the algorithms provided by the literature is, in the worst case, exponential in the size of the game. To deal ...
Introducing alarms in adversarial patrolling games: extended abstract
AAMAS '13: Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems

Adversarial patrolling games (APGs) can be modeled as Stackelberg games where a patroller and an intruder compete. The former moves with the aim of detecting an intrusion, while the latter tries to intrude without being detected. In this paper, we ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

AAMAS '14: Proceedings of the 2014 international conference on Autonomous agents and multi-agent systems

May 2014

1774 pages

ISBN:9781450327381

General Chairs:
Ana Bazzan
UFRGS, Brazil
,
Michael Huhns
University of South Carolina, USA
,
Program Chairs:
Alessio Lomuscio
Imperial College London, UK
,
Paul Scerri
Carnegie Mellon University, USA

In-Cooperation

SIGAI: ACM Special Interest Group on Artificial Intelligence

Publisher

International Foundation for Autonomous Agents and Multiagent Systems

Richland, SC

Publication History

Published: 05 May 2014

Check for updates

Author Tags

Qualifiers

Poster

Conference

AAMAS '14

Sponsor:

AAMAS '14: International conference on Autonomous Agents and Multi-Agent Systems

May 5 - 9, 2014

Paris, France

Acceptance Rates

AAMAS '14 Paper Acceptance Rate 169 of 709 submissions, 24%;

Overall Acceptance Rate 1,155 of 5,036 submissions, 23%

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

4
Total Citations
View Citations
60
Total Downloads

Downloads (Last 12 months)4
Downloads (Last 6 weeks)0

Reflects downloads up to 16 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Gholami SYadav ATran-Thanh LDilkina BTambe MElkind EVeloso MAgmon NTaylor M(2019)Don't Put All Your Strategies in One BasketProceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems10.5555/3306127.3331719(395-403)Online publication date: 8-May-2019
https://dl.acm.org/doi/10.5555/3306127.3331719
Gholami SMc Carthy SDilkina BPlumptre ATambe MDriciru MWanyama FRwetsiba ANsubaga MMabonga JOkello TEnyel EAndre EKoenig SDastani MSukthankar G(2018)Adversary Models Account for Imperfect Crime DataProceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems10.5555/3237383.3237505(823-831)Online publication date: 9-Jul-2018
https://dl.acm.org/doi/10.5555/3237383.3237505
Kar DFord BGholami SFang FPlumptre ATambe MDriciru MWanyama FRwetsiba ANsubaga MMabonga JLarson KWinikoff MDas SDurfee E(2017)Cloudy with a Chance of PoachingProceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems10.5555/3091125.3091153(159-167)Online publication date: 8-May-2017
https://dl.acm.org/doi/10.5555/3091125.3091153
Zhang CBucarey VMukhopadhyay ASinha AQian YVorobeychik YTambe MJonker CMarsella SThangarajah JTuyls K(2016)Using Abstractions to Solve Opportunistic Crime Security Games at ScaleProceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems10.5555/2936924.2936956(196-204)Online publication date: 9-May-2016
https://dl.acm.org/doi/10.5555/2936924.2936956

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

Hard and soft equilibria in boolean games

Local search techniques for computing equilibria in two-player general-sum strategic-form games

Introducing alarms in adversarial patrolling games: extended abstract