Automatic Synthesis of Efficient Regular Strategies in
Adversarial Patrolling Games

D 2018

Automatic Synthesis of Efficient Regular Strategies in Adversarial Patrolling Games

KLAŠKA, David, Antonín KUČERA, Tomáš LAMSER and Vojtěch ŘEHÁK

Basic information

Original name

Automatic Synthesis of Efficient Regular Strategies in Adversarial Patrolling Games

Authors

KLAŠKA, David (203 Czech Republic, belonging to the institution), Antonín KUČERA (203 Czech Republic, belonging to the institution), Tomáš LAMSER (203 Czech Republic, belonging to the institution) and Vojtěch ŘEHÁK (203 Czech Republic, guarantor, belonging to the institution)

Edition

Richland, SC, Proceedings of the 2018 International Conference on Autonomous Agents & Multiagent Systems, p. 659-666, 8 pp. 2018

Publisher

International Foundation for Autonomous Agents and Multiagent Systems

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

References:

URL

RIV identification code

RIV/00216224:14330/18:00100830

Organization unit

Faculty of Informatics

ISBN

978-1-5108-6808-3

ISSN

DOI

http://dx.doi.org/10.5555/3237383.3237481

UT WoS

000468231300081

Keywords in English

patrolling games; single and multi-agent planning and scheduling

Abstract

V originále

We give a polynomial-time algorithm for synthesizing efficient regular strategies in adversarial patrolling games with general topology. Regular strategies use finite memory to gather some relevant information about the history of Defender's moves which results in substantially better protection of the targets. So far, the scope of automatic strategy synthesis was limited to positional strategies (which ignore the history) or to regular strategies where the underlying finite-memory observer had to be supplied manually. Furthermore, the existing methods do not give any information on how far are the constructed strategies from being optimal. In this paper, we try to overcome these limitations. We develop a novel gradient-based algorithm for synthesizing regular strategies where the underlying finite-memory observers are constructed algorithmically. The running time of our algorithm is polynomial which makes the algorithm applicable to instances of realistic size. Furthermore, we develop an algorithm for computing an upper bound on the best achievable protection, and compare the quality of the constructed strategies against this bound. Thus, we can effectively measure the "distance'' of the constructed strategies from optimal strategies, and our experiments show that this distance is often quite small.

Links

GA18-11193S, research and development project

Name: Algoritmy pro diskrétní systémy a hry s nekonečně mnoha stavy

Investor: Czech Science Foundation

MUNI/A/0854/2017, interní kód MU

Name: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace VII.

Investor: Masaryk University, Category A

MUNI/A/1038/2017, interní kód MU

Name: Zapojení studentů Fakulty informatiky do mezinárodní vědecké komunity 18

Investor: Masaryk University, Category A

Citovat

KLAŠKA, David, Antonín KUČERA, Tomáš LAMSER and Vojtěch ŘEHÁK. Automatic Synthesis of Efficient Regular Strategies in Adversarial Patrolling Games. Online. In Proceedings of the 2018 International Conference on Autonomous Agents & Multiagent Systems. Richland, SC: International Foundation for Autonomous Agents and Multiagent Systems, 2018, p. 659-666. ISBN 978-1-5108-6808-3. Available from: https://dx.doi.org/10.5555/3237383.3237481.

@inproceedings{1408461,
   author = {Klaška, David and Kučera, Antonín and Lamser, Tomáš and Řehák, Vojtěch},
   address = {Richland, SC},
   booktitle = {Proceedings of the 2018 International Conference on Autonomous Agents & Multiagent Systems},
   doi = {http://dx.doi.org/10.5555/3237383.3237481},
   keywords = {patrolling games; single and multi-agent planning and scheduling},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {Richland, SC},
   isbn = {978-1-5108-6808-3},
   pages = {659-666},
   publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
   title = {Automatic Synthesis of Efficient Regular Strategies in Adversarial Patrolling Games},
   url = {http://dl.acm.org/citation.cfm?id=3237383.3237481},
   year = {2018}
}

TY  - JOUR
ID  - 1408461
AU  - Klaška, David - Kučera, Antonín - Lamser, Tomáš - Řehák, Vojtěch
PY  - 2018
TI  - Automatic Synthesis of Efficient Regular Strategies in Adversarial Patrolling Games
PB  - International Foundation for Autonomous Agents and Multiagent Systems
CY  - Richland, SC
SN  - 9781510868083
KW  - patrolling games
KW  - single and multi-agent planning and scheduling
UR  - http://dl.acm.org/citation.cfm?id=3237383.3237481
L2  - http://dl.acm.org/citation.cfm?id=3237383.3237481
N2  - We give a polynomial-time algorithm for synthesizing efficient regular strategies in adversarial patrolling games with general topology. Regular strategies use finite memory to gather some relevant information about the history of Defender's moves which results in substantially better protection of the targets. So far, the scope of automatic strategy synthesis was limited to positional strategies (which ignore the history) or to regular strategies where the underlying finite-memory observer had to be supplied manually. Furthermore, the existing methods do not give any information on how far are the constructed strategies from being optimal. In this paper, we try to overcome these limitations. We develop a novel gradient-based algorithm for synthesizing regular strategies where the underlying finite-memory observers are constructed algorithmically. The running time of our algorithm is polynomial which makes the algorithm applicable to instances of realistic size. Furthermore, we develop an algorithm for computing an upper bound on the best achievable protection, and compare the quality of the constructed strategies against this bound. Thus, we can effectively measure the "distance'' of the constructed strategies from optimal strategies, and our experiments show that this distance is often quite small.
ER  -

KLAŠKA, David, Antonín KUČERA, Tomáš LAMSER and Vojtěch ŘEHÁK. Automatic Synthesis of Efficient Regular Strategies in Adversarial Patrolling Games. Online. In \textit{Proceedings of the 2018 International Conference on Autonomous Agents \&{} Multiagent Systems}. Richland, SC: International Foundation for Autonomous Agents and Multiagent Systems, 2018, p.~659-666. ISBN~978-1-5108-6808-3. Available from: https://dx.doi.org/10.5555/3237383.3237481.

Detailed Information on Publication Record