Game Theory and the Navy Budget
Abstract
This is the Phase II follow-up from risk-based decision analysis in capital budgeting and stochastic portfolio optimization. The research purpose is to propose a novel, reusable, extensible, adaptable, and comprehensive advanced analytical process employing strategic game theory with Integrated Risk Management to help the DOD with capital budgeting under uncertainty, with Monte Carlo risk-simulation, predictive analytics, and stochastic portfolio optimization of acquisitions and programs portfolios with multiple competing stakeholders while subject to budgetary, risk,schedule, and strategic constraints. Game theory applications will include areas of repeated finite and infinite games with complete and incomplete information in strategic and extended forms. The research approach will include, when appropriate, theoretical mathematical formulations,recommended data collection/integration, and optimization approaches, as well as practical implementation recommendations to test the benefits and viability of the proposed approach to generate optimal budget allocations and strategies informed by the reactions of other nations or internal players (U.S. Congress, organizations within DOD). The PI is an expert in modeling uncertainty and risk-based stochastic portfolio optimization decision analytics and strategic real options and game theoretical constructs. Whenever appropriate, strategic and extended forms will be applied.The assumption in game theory includes the rationality of the decision makers and updated information using Bayes law. The idea is to analyze Bertrand, Cournot, and Nash equilibria with pure and mixed strategies with dominant and dominated conditions in repeated games to determine the recommended method.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 21, 2023
- Accession Number
- AD1214570
Entities
People
- Jonathan Mun
Organizations
- Naval Postgraduate School