Determination of Fire Control Policies via Approximate Dynamic Programming

Given the ubiquitous nature of both offensive and defensive missile systems, the catastrophe-causing potential they represent, and the limited resources available to countries for missile defense, optimizing the defensive response to a missile attack is a necessary endeavor. For a single salvo of offensive missiles launched at a set of targets, a missile defense system protecting those targets must decide how many interceptors to fire at each incoming missile. Since such missile engagements often involve the firing of more than one attack salvo, we develop a Markov decision process (MDP) model to examine the optimal fire control policy for the defender. Due to the computational intractability of using exact methods for all but the smallest problem instances, we utilize an approximate dynamic programming (ADP) approach to explore the efficacy of applying approximate methods to the problem. We obtain policy insights by analyzing subsets of the state space that reflect a range of possible defender interceptor inventories. Testing of four scenarios demonstrates that the ADP policy provides high-quality decisions for a majority of the state space, achieving a 7.74% mean optimality gap in the baseline scenario. Moreover, computational effort for the ADP algorithm requires only a few minutes versus 12 hours for the exact dynamic programming algorithm, providing a method to address more complex and realistically-sized instances

Investigation of Cooperative Behavior in Autonomous Wide Search Munitions

The purpose of this research is to investigate the effectiveness of wide-area search munitions in various scenarios using different cooperative behavior algorithms. The general scenario involves multiple autonomous munitions searching for an unknown number of targets of different priority in unknown locations. Three cooperative behavior algorithms are used in each scenario: no cooperation, cooperative attack only, and cooperative classification and attack. In the cooperative cases, the munitions allocate tasks on-line as a group, using linear programming techniques to determine the optimum allocation. Each munition provides inputs to the task allocation routine in the form of probabilities of successfully being able to complete the various tasks. These probabilities of success are based on statistical Poisson field theory. Weighting parameters are applied to the probabilities of success so that optimum settings can be determined via Response Surface Methodology. Results are compared within and across the various scenarios. Initial results did not reflect expected behavior (due to poor choice of responses to optimize). Experiments were modified and more desirable results obtained. In general, cooperative engagement alone attacks and kills fewer targets than no cooperation. Cooperative classification however, kills fewer targets at low false target attack rates (\u3c 0.005/sq km), but outperforms the other algorithms as the false target attack rate increases. This is due primarily to the fact that cooperative classification significantly reduces and stabilizes the effective false target attack rate

Surveillance Planning against Smart Insurgents in Complex Terrain

This study is concerned with finding a way to solve a surveillance system allocation problem based on the need to consider intelligent insurgency that takes place in a complex geographical environment. Although this effort can be generalized to other situations, it is particularly geared towards protecting military outposts in foreign lands. The technological assets that are assumed available include stare-devices, such as tower-cameras and aerostats, as well as manned and unmanned aerial systems. Since acquiring these assets depends on the ability to control and monitor them on the target terrain, their operations on the geo-location of interest ought to be evaluated. Such an assessment has to also consider the risks associated with the environmental advantages that are accessible to a smart adversary. Failure to consider these aspects might render the forces vulnerable to surprise attacks. The problem of this study is formulated as follows: given a complex terrain and a smart adversary, what types of surveillance systems, and how many entities of each kind, does a military outpost need to adequately monitor its surrounding environment? To answer this question, an analytical framework is developed and structured as a series of problems that are solved in a comprehensive and realistic fashion. This includes digitizing the terrain into a grid of cell objects, identifying high-risk spots, generating flight tours, and assigning the appropriate surveillance system to the right route or area. Optimization tools are employed to empower the framework in enforcing constraints--such as fuel/battery endurance, flying assets at adequate altitudes, and respecting the climbing/diving rate limits of the aerial vehicles--and optimizing certain mission objectives--e.g. revisiting critical regions in a timely manner, minimizing manning requirements, and maximizing sensor-captured image quality. The framework is embedded in a software application that supports a friendly user interface, which includes the visualization of maps, tours, and related statistics. The final product is expected to support designing surveillance plans for remote military outposts and making critical decisions in a more reliable manner

Modeling Homeland Security: A Value Focused Thinking Approach

The events of September 11, 2001 have propelled the topic of homeland security to the forefront of national concern. The threat of terrorism within the United States has reached an unprecedented level. The pervasive vulnerabilities of the nation\u27s critical infrastructure coupled with the destructive capabilities and deadly intentions of modern terrorists pose extraordinary risks. The United States must mitigate these risks while at the same time balancing the associated costs and impact on civil liberties. Currently, the United States lacks effective methods and measure for assessing the security of the homeland from acts of terrorism. This study outlines a first cut decision analysis methodology for identifying and structuring key homeland security objectives and facilitating the measurement of the United States\u27 capability to execute these objectives

An Evaluation Schema for the Ethical Use of Autonomous Robotic Systems in Security Applications

We propose a multi-step evaluation schema designed to help procurement agencies and others to examine the ethical dimensions of autonomous systems to be applied in the security sector, including autonomous weapons systems

Autonomous Weapons Systems: The ICRC's recommendations and its implications for International Humanitarian Law

This thesis examines the effects of the ICRC recommendations given May 2021 on Autonomous Weapon Systems under the current state of International Humanitarian Law. It also presents a view of how the recommendation might effect the area of AWS going forwards, as well as examining some of the questions relating more specifically to weapon autonomy, and its implication in modern conflicts

High stakes: The role of weapons in offender decision making

This chapter describes the contradictory roles that weapons play in offender decision making as mechanisms that can both increase the physical harm to a victim of violence and also reduce the need for physical harm in victims of robbery. Because weapons serve simultaneously offensive and defensive purposes, the way in which offenders carry and use weapons is subject to a complex decision-making process. This process is presented and interpreted from a rational perspective, incorporating an offender’s calculation of potential benefits and costs as well as the uncertainty of a victim’s response. A rational analysis of weapon carrying and use is presented along with research evidence suggesting that culture and availability are important influences on weapon of choice and weapon-related behavior. The chapter concludes with a review of the effectiveness of weapons in reducing victim resistance and retaliation showing that weapon use is a high-reward/high-cost activity

The salvo combat model with area fire

This paper analyzes versions of the salvo model of missile combat where area fire is used by one or both sides in a battle. While these models share some properties with the area fire Lanchester model and the aimed fire salvo model, they also display some interesting differences, especially over the course of several salvos. Whereas the relative size of each force is important with aimed fire, with area fire it is the absolute size that matters. Similarly, while aimed fire exhibits square law behavior, area fire shows approximately linear behavior. When one side uses area and the other uses aimed fire, the model displays a mix of square and linear law behavior