Interactive Execution Monitoring of Agent Teams

There is an increasing need for automated support for humans monitoring the activity of distributed teams of cooperating agents, both human and machine. We characterize the domain-independent challenges posed by this problem, and describe how properties of domains influence the challenges and their solutions. We will concentrate on dynamic, data-rich domains where humans are ultimately responsible for team behavior. Thus, the automated aid should interactively support effective and timely decision making by the human. We present a domain-independent categorization of the types of alerts a plan-based monitoring system might issue to a user, where each type generally requires different monitoring techniques. We describe a monitoring framework for integrating many domain-specific and task-specific monitoring techniques and then using the concept of value of an alert to avoid operator overload. We use this framework to describe an execution monitoring approach we have used to implement Execution Assistants (EAs) in two different dynamic, data-rich, real-world domains to assist a human in monitoring team behavior. One domain (Army small unit operations) has hundreds of mobile, geographically distributed agents, a combination of humans, robots, and vehicles. The other domain (teams of unmanned ground and air vehicles) has a handful of cooperating robots. Both domains involve unpredictable adversaries in the vicinity. Our approach customizes monitoring behavior for each specific task, plan, and situation, as well as for user preferences. Our EAs alert the human controller when reported events threaten plan execution or physically threaten team members. Alerts were generated in a timely manner without inundating the user with too many alerts (less than 10 percent of alerts are unwanted, as judged by domain experts)

Ten propositions about public leadership

Purpose – The purpose of this paper is to provide an overview of some pressing but under-researched aspects of public leadership. Ten propositions about public leadership are set out and these are intended to be thought-provoking and even controversial in order to stimulate researchers to design research which addresses key theoretical and practical questions about leadership in the public sphere. They will also help practitioners navigate an increasingly complex leadership context. Design/methodology/approach – This invited essay uses ten propositions about public leadership, selected from three sources: the leadership literature, the author’s own research and from collaborative research discussions with academics, policy makers and practitioners. Findings – The first proposition argues for distinguishing public leadership from public service leadership given that the former is about leadership of the public sphere. Other propositions concern context; purpose; conflict and contest at the heart of public leadership; leadership with political astuteness; dual leadership; leadership projections; fostering resilience; leadership, authority and legitimacy; and the challenge to researchers to use research designs which reflect the complexity and dynamism of public leadership. Practical implications – While this essay is primarily addressed to researchers, there are many ideas and concepts which practising leaders will find insightful and useful in their work. Originality/value – This essay draws on deep experience in undertaking high-quality academic research about public leadership which draws from and feeds into policy and practice. It utilises organisational psychology, public management and political science to create synergies in order to enhance the understanding of public leadership

AI-AUGMENTED DECISION SUPPORT SYSTEMS: APPLICATION IN MARITIME DECISION MAKING UNDER CONDITIONS OF METOC UNCERTAINTY

The ability for a human to overlay information from disparate sensor systems or remote databases into a common operational picture can enhance rapid decision making and implementation in a complex environment. This thesis focuses on operational uncertainty as a function of meteorological and oceanographic (METOC) effects on maritime route planning. Using an existing decision support system (DSS) with artificial intelligence (AI) algorithms developed by New Jersey Institute of Technology and University of Connecticut, cognitive load and time to decision were assessed for users of an AI-augmented DSS, accounting for METOC conditions and their effects, and users of a baseline, 'as is,' DSS system. Scenario uncertainty for the user was presented in the relative number of Pareto-optimal routes from two locations. Key results were (a) users of an AI-augmented DSS with a simplified interface completed assigned tasks in significantly less time than users of an information-dense, complex-interface AI-augmented DSS; (b) users of simplified, AI-augmented DSS arrived at decisions with lower cognitive load than baseline DSS and complex-interface AI-augmented DSS users; and (c) users relied mainly on quantitative data presented in tabular form to make route decisions. The differences found in user performance and cognitive load between levels of AI augmentation and interface complexity serve as a starting point for further exploration into maximizing the potential of human-machine teaming.Office of Naval ResearchMajor, United States Marine CorpsApproved for public release. distribution is unlimite

Resilient Aircraft Sustainment: Quantifying Resilience through Asset and Capacity Allocation

Decision makers lack a clear, generalizable method to quantify how additional investment in inventory and capacity equates to additional levels of resilience. This research facilitates a deeper understanding of the intricacies and complex interconnectedness of organizational supply chains by monetarily quantifying changes in network resilience. The developed Area under the Curve metric (AUC) is used to quantify the level of demand that each asset allocation can meet during a disruptive event. Due to its applicability across multiple domains, the USAF F-16 repair network in the Pacific theater (PACAF) is modeled utilizing discrete event simulation and used as the illustrating example. This research uses various levels of production capacity and response time as the primary resilience levers. However, it is essential to simultaneously invest in inventory and capacity to realize the greatest impacts on resilience. Real-world demand and cost data are incorporated to identify the inherent cost-resilience relationships, essential for evaluating the response and recovery capabilities across the developed scenarios. Results indicate that recovery capacity and response time are the greatest drivers of recovery after a disruption. Additionally, numerous network designs employing various levels of design flexibility are evaluated and recommended for future capacity expansion

PERFORMANCE EVALUATION AND REVIEW FRAMEWORK OF ROBOTIC MISSIONS (PERFORM): AUTONOMOUS PATH PLANNING AND AUTONOMY PERFORMANCE EVALUATION

The scope of this work spans two main areas of autonomy research 1) autonomous path planning and 2) test and evaluation of autonomous systems. Path planning is an integral part of autonomous decision-making, and a deep understanding in this area provides valuable perspective on approaching the problem of how to effectively evaluate vehicle behavior. Autonomous decision-making capabilities must include reliability, robustness, and trustworthiness in a real-world environment. A major component of robot decision-making lies in intelligent path-planning. Serving as the brains of an autonomous system, an efficient and reliable path planner is crucial to mission success and overall safety. A hybrid global and local planner is implemented using a combination of the Potential Field Method (PFM) and A-star (A*) algorithms. Created using a layered vector field strategy, this allows for flexibility along with the ability to add and remove layers to take into account other parameters such as currents, wind, dynamics, and the International Regulations for Preventing Collisions at Sea (COLGREGS). Different weights can be attributed to each layer based on the determined level of importance in a hierarchical manner. Different obstacle scenarios are shown in simulation, and proof-of-concept validation of the path-planning algorithms on an actual ASV is accomplished in an indoor environment. Results show that the combination of PFM and A* complement each other to generate a successfully planned path to goal that alleviates local minima and entrapment issues. Additionally, the planner demonstrates the ability to update for new obstacles in real time using an obstacle detection sensor. Regarding test and evaluation of autonomous vehicles, trust and confidence in autonomous behavior is required to send autonomous vehicles into operational missions. The author introduces the Performance Evaluation and Review Framework Of Robotic Missions (PERFORM), a framework for which to enable a rigorous and replicable autonomy test environment, thereby filling the void between that of merely simulating autonomy and that of completing true field missions. A generic architecture for defining the missions under test is proposed and a unique Interval Type-2 Fuzzy Logic approach is used as the foundation for the mathematically rigorous autonomy evaluation framework. The test environment is designed to aid in (1) new technology development (i.e. providing direct comparisons and quantitative evaluations of varying autonomy algorithms), (2) the validation of the performance of specific autonomous platforms, and (3) the selection of the appropriate robotic platform(s) for a given mission type (e.g. for surveying, surveillance, search and rescue). Several case studies are presented to apply the metric to various test scenarios. Results demonstrate the flexibility of the technique with the ability to tailor tests to the user’s design requirements accounting for different priorities related to acceptable risks and goals of a given mission

Prospective for urban informatics

The specialization of different urban sectors, theories, and technologies and their confluence in city development have led to a greatly accelerated growth in urban informatics, the transdisciplinary field for understanding and developing the city through new information technologies. While this young and highly promising field has attracted multiple reviews of its advances and outlook for its future, it would be instructive to probe further into the research initiatives of this rapidly evolving field, to provide reference to the development of not only urban informatics, but moreover the future of cities as a whole. This article thus presents a collection of research initiatives for urban informatics, based on the reviews of the state of the art in this field. The initiatives cover three levels, namely the future of urban science; core enabling technologies including geospatial artificial intelligence, high-definition mapping, quantum computing, artificial intelligence and the internet of things (AIoT), digital twins, explainable artificial intelligence, distributed machine learning, privacy-preserving deep learning, and applications in urban design and planning, transport, location-based services, and the metaverse, together with a discussion of algorithmic and data-driven approaches. The article concludes with hopes for the future development of urban informatics and focusses on the balance between our ever-increasing reliance on technology and important societal concerns

U.S. AND PRC STRATEGIC COMPETITION: CYBER AND RISK AVERSION

The People’s Republic of China (PRC) altered its calculations from the aftermath of the 1990 Persian Gulf war and placed emphasis on the importance of technology and information. The PRC created the Strategic Support Force (SSF), which became operational in 2015, and includes space, cyber, and electronic warfare capabilities under one command. Meanwhile, the U.S. has wrapped itself in structural and cultural limitations, which hinder operational tempo. This thesis examined how the Department of Defense can adjust its positions on Cyber Titles, authorities, permissions, and risk aversion in leadership to maintain a competitive edge against the threat of the PRC’s SSF in the cyber domain. This thesis used system dynamics to model the economies of both the U.S. and the PRC into cyber capabilities, which resulted in an understanding that allocating additional money alone will not solve the core issue. Understanding the limitations of cultural biases, and using decision-making tools such as prospect theory, leaders can make more effective decisions. Through proper education of staff officers about cyber capabilities and their effects, integration of cyber operations at combat training centers, and pushing permissions and rules of engagements down to Task Force Commanders, the U.S. can overcome the structural and cultural obstacles.Major, United States ArmyMajor, United States Marine CorpsApproved for public release. Distribution is unlimited

Can we get there from here? Ecosystem based governance in the Bay of Fundy/Gulf of Maine region

Decades, even centuries, of resource extraction and exploitation by humans have taken a toll on the Bay of Fundy/Gulf of Maine ecosystems. The very real threats posed by population growth and coastal development, climate change, habitat loss, overharvesting, chemical pollution, nutrient overloading, and invasive species invasions show no sign of abating. Traditional methods of managing the human activities that impact the Bay of Fundy/Gulf of Maine are proving unable to keep pace with the growing threats. The Gulf of Maine Council and others have joined in the chorus calling for a broader, more holistic ecosystem approach to the governance of the human activities that impact the coastal margin. This study uses the framework of the Policy Sciences to suggest a model of Problem Orientation, Social Process, and Decision Process characteristics indicative of an ideal ecosystem-based approach to governance. The model is first used to analyze the governance regime that existed in the Great Lakes Basin during the first two decades under the International Joint Commission\u27s oversight of activities under the Great Lakes Water Quality Agreement. The framework model is then used to analyze the current governance regime in the Gulf of Maine/Bay of Fundy region. Using this analysis, the study concludes that an ecosystem-based approach to governance is not possible in the region as currently configured. The study further concludes that it will not be possible to transition to an ecosystem-based approach without the education and significant outreach necessary to create a knowledgeable and activist public able to understand the issues and threats and willing to press governance for improvement. Further, ecosystem-based governance will require the creation of an overarching and accountable entity that, with significant input from public and stakeholder partnerships can collect reliable ecosystem indicator data from both sides of the border, analyze the data, and direct the implementation of policy solutions, and change course as necessary

Considerations in Assuring Safety of Increasingly Autonomous Systems

Recent technological advances have accelerated the development and application of increasingly autonomous (IA) systems in civil and military aviation. IA systems can provide automation of complex mission tasks-ranging across reduced crew operations, air-traffic management, and unmanned, autonomous aircraft-with most applications calling for collaboration and teaming among humans and IA agents. IA systems are expected to provide benefits in terms of safety, reliability, efficiency, affordability, and previously unattainable mission capability. There is also a potential for improving safety by removal of human errors. There are, however, several challenges in the safety assurance of these systems due to the highly adaptive and non-deterministic behavior of these systems, and vulnerabilities due to potential divergence of airplane state awareness between the IA system and humans. These systems must deal with external sensors and actuators, and they must respond in time commensurate with the activities of the system in its environment. One of the main challenges is that safety assurance, currently relying upon authority transfer from an autonomous function to a human to mitigate safety concerns, will need to address their mitigation by automation in a collaborative dynamic context. These challenges have a fundamental, multidimensional impact on the safety assurance methods, system architecture, and V&V capabilities to be employed. The goal of this report is to identify relevant issues to be addressed in these areas, the potential gaps in the current safety assurance techniques, and critical questions that would need to be answered to assure safety of IA systems. We focus on a scenario of reduced crew operation when an IA system is employed which reduces, changes or eliminates a human's role in transition from two-pilot operations