FlipDyn in Graphs: Resource Takeover Games in Graphs
Sandeep Banik, Shaunak D. Bopardikar, Naira Hovakimyan

TL;DR
This paper extends the FlipDyn game framework to graph-based settings, modeling strategic node takeover in dynamical systems to analyze Nash equilibria and derive strategies for scalar linear systems and Markov chains.
Contribution
It introduces a graph-based FlipDyn model for dynamical systems, characterizes Nash equilibria, and derives analytical strategies for scalar linear systems and Markov chains.
Findings
Derived NE strategies for scalar linear systems.
Provided analytical expressions for Markov chain cases.
Numerical illustrations with epidemic and linear systems.
Abstract
We present \texttt{FlipDyn-G}, a dynamic game model extending the \texttt{FlipDyn} framework to a graph-based setting, where each node represents a dynamical system. This model captures the interactions between a defender and an adversary who strategically take over nodes in a graph to minimize (resp. maximize) a finite horizon additive cost. At any time, the \texttt{FlipDyn} state is represented as the current node, and each player can transition the \texttt{FlipDyn} state to a depending based on the connectivity from the current node. Such transitions are driven by the node dynamics, state, and node-dependent costs. This model results in a hybrid dynamical system where the discrete state (\texttt{FlipDyn} state) governs the continuous state evolution and the corresponding state cost. Our objective is to compute the Nash equilibrium of this finite horizon zero-sum game on a graph. Our…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsGame Theory and Applications · Auction Theory and Applications · Blockchain Technology Applications and Security
