Technology Category
Search and Optimization: Adversarial SearchGame Theory and Economic Paradigms: Adversarial LearningConstraint Satisfaction and Optimization: Search
Strategic hiding and exploration in networks
🤖 AI Summary
This paper studies the adversarial network hiding game: a hider constructs a connected network under an edge-budget constraint and conceals a target, while a searcher—starting from a fixed node and unaware of both the network topology and target location—employs an expanding search strategy. We formulate a game-theoretic model jointly optimizing network design and search policy. First, we characterize the Nash equilibrium structure on trees, deriving analytical properties of the hider’s optimal tree topology and the searcher’s optimal expanding search path. Second, we establish a tight upper bound on the expected number of steps required for successful search. Third, we extend the analysis to unicyclic networks (i.e., graphs containing exactly one cycle), providing a theoretical upper bound on search steps. Our results reveal the coupled influence of network connectivity, centrality measures, and edge-budget constraints on search efficiency, offering foundational insights for secure network design and robust adversarial search.
Technology Category
Application Category
📝 Abstract
We propose and study a model of strategic network design and exploration where the hider, subject to a budget constraint restricting the number of links, chooses a connected network and the location of an object. Meanwhile, the seeker, not observing the network and the location of the object, chooses a network exploration strategy starting at a fixed node in the network. The network exploration follows the expanding search paradigm of Alpern and Lidbetter (2013). We obtain a Nash equilibrium and characterize equilibrium payoffs in the case of linking budget allowing for trees only. We also give an upper bound on the expected number of steps needed to find the hider for the case where the linking budget allows for at most one cycle in the network.
Problem
Research questions and friction points this paper is trying to address.
Strategic network design with budget-constrained link choices
Network exploration under incomplete information about object location
Equilibrium analysis for tree structures and single-cycle networks
Innovation
Methods, ideas, or system contributions that make the work stand out.
Strategic network design with budget constraints
Expanding search paradigm for network exploration
Nash equilibrium analysis for tree structures
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