Title
Privacy-aware stochastic control with a “snoopy” adversary: A game-theoretic approach
Abstract
We consider a scenario in which a controller and an adversary dynamically act on a system over a finite or infinite horizon. The controller and the adversary do not want to reveal their actions to each other, and at the same time, the controller acts to minimize an expected cost, and the adversary acts to maximize it. We model this scenario as a dynamic zero-sum game, prove the existence of a unique saddle-point equilibrium, and devise an algorithm to compute the equilibrium for finite and infinite horizon settings.
Year
DOI
Venue
2016
10.1109/CISS.2016.7460499
2016 Annual Conference on Information Science and Systems (CISS)
Keywords
Field
DocType
privacy-aware stochastic control,snoopy adversary,game-theoretic approach,infinite horizon,finite horizon,dynamic zero-sum game,saddle-point equilibrium
Control theory,Mathematical optimization,Computer science,Adversary model,Repeated game,Game theory,Adversary,Example of a game without a value,Stochastic game,Stochastic control
Conference
Citations 
PageRank 
References 
0
0.34
3
Authors
1
Name
Order
Citations
PageRank
Abhishek Gupta11410.61