A Quantitative Framework for the Road-mapping of Autonomous Defense Technologies

Technology roadmapping serves as a strategic tool to support robust methods of allocating resources across various technological domains. This study introduces a game-theoretic model to simulate the evolutionary trajectories of autonomous defense systems, steered by the investment decisions of two competing sovereign actors within a shared strategic environment. The model identifies optimal strategies for technological advancement, represented by equilibrium states in a zero-sum military simulation. To approximate the selection of these optimal pathways, Local Symplectic Surgery (LSS) is employed, with its payoff evaluated by the likelihood of victory in simulated combat scenarios. Finally, a case is studied to demonstrate the feasibility of the proposed approach.