Network-Enabled Missile Deflection: Games and Correlation Equilibrium

The problem of deploying countermeasures (CM) against antiship missiles is investigated from a network centric perspective in which multiple ships coordinate to defend against a known missile threat. Using the paradigm of network enabled operations (NEOPS), the problem is formulated as a transient stochastic game with communication where the appropriate strategy takes the form of an optimal stationary correlated equilibrium. Under this strategy, ships cooperate through real-time communication to satisfy both local and collective interests. The use of communication results in a performance improvement over the noncommunicating, Nash equilibrium scenario. This framework allows us to develop a theoretical foundation for NEOPS and captures the trade-off between information exchange and performance, while generalizing the standard Nash equilibrium solution for the missile deflection game given in [1], The NEOPS equilibrium strategy is characterized as the solution to an optimization problem with linear objective and bilinear constraints, which can be solved calculating successive improvements starting from an initial noncooperative (Nash) solution. The communication overhead required to implement this strategy is associated with the mutual information between individual action probability distributions at equilibrium. Numerical results illustrate the trade-off between communication and performance.     

Decentralized algorithms for netcentric force protection against antiship missiles

We model a decentralized network of decision makers charged with optimally deploying hardkill and/or softkill weapons (countermeasures (CMs)) to defend a task group from antiship missiles. Each platform (decision maker) observes missile threats using a combination of shipboard sensor measurement data and data from other ships, but acts independently when controlling its own weapon systems to cooperatively pursue the defensive objectives of the task group in a decentralized fashion. The main results are a formulation of the missile deflection problem as a stochastic shortest path Markovian game with constraints, a characterization of the Nash equilibrium solution, and a decentralized algorithm for computing the Nash equilibrium when the stochastic game is collaborative. Numerical examples are given to demonstrate the equilibrium policies and illustrate their sensitivity to the missile dynamics.