Game Theory and Prescriptive Analytics for Naval Wargaming Battle Management Aids

NPS NRP Executive SummaryThe Navy is taking advantage of advances in computational technologies and data analytic methods to automate and enhance tactical decisions and support warfighters in highly complex combat environments. Novel automated techniques offer opportunities to support the tactical warfighter through enhanced situational awareness, automated reasoning and problem-solving, and faster decision timelines. This study will investigate how game theory and prescriptive analytics methods can be used to develop real-time wargaming capabilities to support warfighters in their ability to explore and evaluate the possible consequences of different tactical COAs to improve tactical missions. This study will develop a conceptual design of a real-time tactical wargaming capability. This study will explore data analytic methods including game theory, prescriptive analytics, and artificial intelligence (AI) to evaluate their potential to support real-time wargaming.N2/N6 - Information WarfareThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Game Theory and Prescriptive Analytics for Naval Wargaming Battle Management Aids

NPS NRP Technical ReportThe Navy is taking advantage of advances in computational technologies and data analytic methods to automate and enhance tactical decisions and support warfighters in highly complex combat environments. Novel automated techniques offer opportunities to support the tactical warfighter through enhanced situational awareness, automated reasoning and problem-solving, and faster decision timelines. This study will investigate how game theory and prescriptive analytics methods can be used to develop real-time wargaming capabilities to support warfighters in their ability to explore and evaluate the possible consequences of different tactical COAs to improve tactical missions. This study will develop a conceptual design of a real-time tactical wargaming capability. This study will explore data analytic methods including game theory, prescriptive analytics, and artificial intelligence (AI) to evaluate their potential to support real-time wargaming.N2/N6 - Information WarfareThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Game Theory and Prescriptive Analytics for Naval Wargaming Battle Management Aids

NPS NRP Project PosterThe Navy is taking advantage of advances in computational technologies and data analytic methods to automate and enhance tactical decisions and support warfighters in highly complex combat environments. Novel automated techniques offer opportunities to support the tactical warfighter through enhanced situational awareness, automated reasoning and problem-solving, and faster decision timelines. This study will investigate how game theory and prescriptive analytics methods can be used to develop real-time wargaming capabilities to support warfighters in their ability to explore and evaluate the possible consequences of different tactical COAs to improve tactical missions. This study will develop a conceptual design of a real-time tactical wargaming capability. This study will explore data analytic methods including game theory, prescriptive analytics, and artificial intelligence (AI) to evaluate their potential to support real-time wargaming.N2/N6 - Information WarfareThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Considerations for Cross Domain / Mission Resource Allocation and Replanning

NPS NRP Executive SummaryNaval platforms are inherently multi-mission - they execute a variety of missions simultaneously. Ships, submarines, and aircraft support multiple missions across domains, such as integrated air and missile defense, ballistic missile defense, anti-submarine warfare, strike operations, naval fires in support of ground operations, and intelligence, surveillance, and reconnaissance. Scheduling and position of these multi-mission platforms is problematic since one warfare area commander desires one position and schedule, while another may have a completely different approach. Commanders struggle to decide and adjudicate these conflicts, because there is plenty of uncertainty about the enemy and the environment. This project will explore emerging innovative data analytic technologies to optimize naval resource allocation and replanning across mission domains. NPS proposes a study that will evaluate the following three solution concepts for this application: (1) game theory, (2) machine learning, and (3) wargaming. The study will first identify a set of operational scenarios that involve distributed and diverse naval platforms and resources and a threat situation that requires multiple concurrent missions in multiple domains. The NPS team will use these scenarios to evaluate the three solution concepts and their applicability to supporting resource allocation and replanning. This project will provide valuable insights into innovative data analytic solution concepts to tackle the Navy's challenge of conducing multiple missions with cross-domain resources.N2/N6 - Information WarfareThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Considerations for Cross Domain / Mission Resource Allocation and Replanning

NPS NRP Technical ReportNaval platforms are inherently multi-mission - they execute a variety of missions simultaneously. Ships, submarines, and aircraft support multiple missions across domains, such as integrated air and missile defense, ballistic missile defense, anti-submarine warfare, strike operations, naval fires in support of ground operations, and intelligence, surveillance, and reconnaissance. Scheduling and position of these multi-mission platforms is problematic since one warfare area commander desires one position and schedule, while another may have a completely different approach. Commanders struggle to decide and adjudicate these conflicts, because there is plenty of uncertainty about the enemy and the environment. This project will explore emerging innovative data analytic technologies to optimize naval resource allocation and replanning across mission domains. NPS proposes a study that will evaluate the following three solution concepts for this application: (1) game theory, (2) machine learning, and (3) wargaming. The study will first identify a set of operational scenarios that involve distributed and diverse naval platforms and resources and a threat situation that requires multiple concurrent missions in multiple domains. The NPS team will use these scenarios to evaluate the three solution concepts and their applicability to supporting resource allocation and replanning. This project will provide valuable insights into innovative data analytic solution concepts to tackle the Navy's challenge of conducing multiple missions with cross-domain resources.N2/N6 - Information WarfareThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Considerations for Cross Domain / Mission Resource Allocation and Replanning

NPS NRP Project PosterNaval platforms are inherently multi-mission - they execute a variety of missions simultaneously. Ships, submarines, and aircraft support multiple missions across domains, such as integrated air and missile defense, ballistic missile defense, anti-submarine warfare, strike operations, naval fires in support of ground operations, and intelligence, surveillance, and reconnaissance. Scheduling and position of these multi-mission platforms is problematic since one warfare area commander desires one position and schedule, while another may have a completely different approach. Commanders struggle to decide and adjudicate these conflicts, because there is plenty of uncertainty about the enemy and the environment. This project will explore emerging innovative data analytic technologies to optimize naval resource allocation and replanning across mission domains. NPS proposes a study that will evaluate the following three solution concepts for this application: (1) game theory, (2) machine learning, and (3) wargaming. The study will first identify a set of operational scenarios that involve distributed and diverse naval platforms and resources and a threat situation that requires multiple concurrent missions in multiple domains. The NPS team will use these scenarios to evaluate the three solution concepts and their applicability to supporting resource allocation and replanning. This project will provide valuable insights into innovative data analytic solution concepts to tackle the Navy's challenge of conducing multiple missions with cross-domain resources.N2/N6 - Information WarfareThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Surviving the crash: assessing the aftermath of cosmic bubble collisions

This paper is the third in a series investigating the possibility that if we reside in an inflationary "bubble universe", we might observe the effects of collisions with other such bubbles. Here, we study the interior structure of a bubble collision spacetime, focusing on the issue of where observers can reside. Numerical simulations indicate that if the inter-bubble domain wall accelerates away, infinite spacelike surfaces of homogeneity develop to the future of the collision; this strongly suggests that observers can have collisions to their past, and previous results then imply that this is very likely. However, for observers at nearly all locations, the restoration of homogeneity relegates any observable effects to a vanishingly small region on the sky. We find that bubble collisions may also play an important role in defining measures in inflation: a potentially infinite relative volume factor arises between two bubble types depending on the sign of the acceleration of the domain wall between them; this may in turn correlate with observables such as the scale or type of inflation.Comment: 19 pages with 13 embedded figures. Improved discussion of the implications for observability and the measure, added reference

Non-detection of previously reported transits of HD 97658b with MOST photometry

The radial velocity-discovered exoplanet HD 97658b was recently announced to transit, with a derived planetary radius of 2.93 \pm 0.28 R_{Earth}. As a transiting super-Earth orbiting a bright star, this planet would make an attractive candidate for additional observations, including studies of its atmospheric properties. We present and analyze follow-up photometric observations of the HD 97658 system acquired with the MOST space telescope. Our results show no transit with the depth and ephemeris reported in the announcement paper. For the same ephemeris, we rule out transits for a planet with radius larger than 2.09 R_{Earth}, corresponding to the reported 3\sigma lower limit. We also report new radial velocity measurements which continue to support the existence of an exoplanet with a period of 9.5 days, and obtain improved orbital parameters.Comment: 16 pages, 4 figures; 1 Table; accepted for publication in ApJL, includes changes made in response to the referee repor

Effects of Turbulence, Eccentricity Damping, and Migration Rate on the Capture of Planets into Mean Motion Resonance

Pairs of migrating extrasolar planets often lock into mean motion resonance as they drift inward. This paper studies the convergent migration of giant planets (driven by a circumstellar disk) and determines the probability that they are captured into mean motion resonance. The probability that such planets enter resonance depends on the type of resonance, the migration rate, the eccentricity damping rate, and the amplitude of the turbulent fluctuations. This problem is studied both through direct integrations of the full 3-body problem, and via semi-analytic model equations. In general, the probability of resonance decreases with increasing migration rate, and with increasing levels of turbulence, but increases with eccentricity damping. Previous work has shown that the distributions of orbital elements (eccentricity and semimajor axis) for observed extrasolar planets can be reproduced by migration models with multiple planets. However, these results depend on resonance locking, and this study shows that entry into -- and maintenance of -- mean motion resonance depends sensitively on migration rate, eccentricity damping, and turbulence.Comment: 43 pages including 14 figures; accepted for publication in The Astrophysical Journa