Efficient computation of discounted asymmetric information zero-sum stochastic games

Handle URI:
http://hdl.handle.net/10754/600891
Title:
Efficient computation of discounted asymmetric information zero-sum stochastic games
Authors:
Li, Lichun; Shamma, Jeff S. ( 0000-0001-5638-9551 )
Abstract:
In asymmetric information zero-sum games, one player has superior information about the game over the other. Asymmetric information games are particularly relevant for security problems, e.g., where an attacker knows its own skill set or alternatively a system administrator knows the state of its resources. In such settings, the informed player is faced with the tradeoff of exploiting its superior information at the cost of revealing its superior information. This tradeoff is typically addressed through randomization, in an effort to keep the uninformed player informationally off balance. A lingering issue is the explicit computation of such strategies. This paper, building on prior work for repeated games, presents an LP formulation to compute suboptimal strategies for the informed player in discounted asymmetric information stochastic games in which state transitions are not affected by the uninformed player. Furthermore, the paper presents bounds between the security level guaranteed by the sub-optimal strategy and the optimal value. The results are illustrated on a stochastic intrusion detection problem.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Citation:
Li, L. and Shamma, J.S., 2015, December. Efficient computation of discounted asymmetric information zero-sum stochastic games. In Decision and Control (CDC), 2015 IEEE 54th Annual Conference on (pp. 4531-4536). IEEE.
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
2015 54th IEEE Conference on Decision and Control (CDC)
Conference/Event name:
2015 54th IEEE Conference on Decision and Control (CDC)
Issue Date:
15-Dec-2015
DOI:
10.1109/CDC.2015.7402927
Type:
Conference Paper
Additional Links:
http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7402927
Appears in Collections:
Conference Papers; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorLi, Lichunen
dc.contributor.authorShamma, Jeff S.en
dc.date.accessioned2016-03-08T13:28:00Zen
dc.date.available2016-03-08T13:28:00Zen
dc.date.issued2015-12-15en
dc.identifier.citationLi, L. and Shamma, J.S., 2015, December. Efficient computation of discounted asymmetric information zero-sum stochastic games. In Decision and Control (CDC), 2015 IEEE 54th Annual Conference on (pp. 4531-4536). IEEE.en
dc.identifier.doi10.1109/CDC.2015.7402927en
dc.identifier.urihttp://hdl.handle.net/10754/600891en
dc.description.abstractIn asymmetric information zero-sum games, one player has superior information about the game over the other. Asymmetric information games are particularly relevant for security problems, e.g., where an attacker knows its own skill set or alternatively a system administrator knows the state of its resources. In such settings, the informed player is faced with the tradeoff of exploiting its superior information at the cost of revealing its superior information. This tradeoff is typically addressed through randomization, in an effort to keep the uninformed player informationally off balance. A lingering issue is the explicit computation of such strategies. This paper, building on prior work for repeated games, presents an LP formulation to compute suboptimal strategies for the informed player in discounted asymmetric information stochastic games in which state transitions are not affected by the uninformed player. Furthermore, the paper presents bounds between the security level guaranteed by the sub-optimal strategy and the optimal value. The results are illustrated on a stochastic intrusion detection problem.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=7402927en
dc.rights(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.en
dc.titleEfficient computation of discounted asymmetric information zero-sum stochastic gamesen
dc.typeConference Paperen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journal2015 54th IEEE Conference on Decision and Control (CDC)en
dc.conference.date15-18 Dec. 2015en
dc.conference.name2015 54th IEEE Conference on Decision and Control (CDC)en
dc.conference.locationOsakaen
dc.eprint.versionPost-printen
dc.contributor.institutiondepartment of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30308, USAen
dc.contributor.institutionSchool of Electrical and Computer Engineering, Georgia Institute of Technologyen
kaust.authorShamma, Jeff S.en
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