Competition-Based Resilience in Distributed Quadratic Optimization
We propose a competition-based approach to resilient distributed optimization with quadratic costs in Networked Control Systems (e.g., wireless sensor network, power grid, robotic team) where a fraction of agents may misbehave (through, e.g., hacking or power outage). Departing from classical filtering strategies proposed in literature, and inspired by a game-theoretic interpretation of consensus,