A Collective Adaptive Approach to Decentralised k-Coverage in Multi-robot Systems

We focus on the online multi-object k-coverage problem (OMOkC), where mobile robots are required to sense a mobile target from k diverse points of view, coordinating themselves in a scalable and possibly decentralised way. There is active research on OMOkC, particularly in the design of decentralised algorithms for solving it. We propose a new take on the issue: Rather than classically developing new algorithms, we apply a macro-level paradigm, called aggregate computing, specifically designed to directly program the global behaviour of a whole ensemble of devices at once. To understand the potential of the application of aggregate computing to OMOkC, we extend the Alchemist simulator (supporting aggregate computing natively) with a novel toolchain component supporting the simulation of mobile robots. This way, we build a software engineering toolchain comprising language and simulation tooling for addressing OMOkC. Finally, we exercise our approach and related toolchain by introducing new algorithms for OMOkC; we show that they can be expressed concisely, reuse existing software components and perform better than the current state-of-the-art in terms of coverage over time and number of objects covered overall

Finding AI Faces in the Moon and Armies in the Clouds : Anthropomorphizing Artificial Intelligence in Military Human-Machine Interactions

Open Access via the T&F AgreementPeer reviewedPublisher PD

Distributed autonomy and trade-offs in online multiobject k-coverage

In this article, we explore the online multiobject k-coverage problem in visual sensor networks. This problem combines k-coverage and the cooperative multirobot observation of multiple moving targets problem, and thereby captures key features of rapidly deployed camera networks, including redundancy and team-based tracking of evasive or unpredictable targets. The benefits of using mobile cameras are demonstrated and we explore the balance of autonomy between cameras generating new subgoals, and those responders able to fulfill them. We show that higher performance against global goals is achieved when decisions are delegated to potential responders who treat subgoals as optional, rather than as obligations that override existing goals without question. This is because responders have up-to-date knowledge of their own state and progress toward goals where they are situated, which is typically old or incomplete at locations remote from them. Examining the extent to which approaches overprovision or underprovision coverage, we find that being well suited for achieving 1-coverage does not imply good performance at k-coverage. Depending on the structure of the environment, the problems of 1-coverage and k-coverage are not necessarily aligned and that there is often a trade-off to be made between standard coverage maximization and achieving k-coverage

Foundations of Trusted Autonomy

Trusted Autonomy; Automation Technology; Autonomous Systems; Self-Governance; Trusted Autonomous Systems; Design of Algorithms and Methodologie

A Widening Attack Plain

A glimpse of our digital future includes diverse actors operating on a widening attack plain with affects ranging from data disruption to death and destruction. How do we craft meaningful narratives of the future that can advise our community today? How do we combat the weaponization of data and future technology? Where do we even start? Threatcasting is a conceptual framework and process that enables multidisciplinary groups to envision and systematically plan against threats ten years in the future. In August 2016, the Army Cyber Institute convened a cross section of public, private and academic participants to model future digital threats using this process with inputs from social science, technical research, cultural history, economics, trends, expert interviews and even a little science fiction. Renowned futurist Brian David Johnson and Army Major Natalie Vanatta will explore the results of this project that not only describes tomorrow’s threats but also identifies specific actions, indicators and concrete steps that can be taken today to disrupt, mitigate and recover from these future threats.https://digitalcommons.usmalibrary.org/aci_books/1034/thumbnail.jp

Beyond goal-rationality:Traditional action can reduce volatility in socially situated agents

Systems that pursue their own goals in shared environments can indirectly affect one another in unanticipated ways, such that the actions of other systems can interfere with goal-achievement. As humans have evolved to achieve goals despite interference from others in society, we thus endow socially situated agents with the capacity for social action as a means of mitigating interference in co-existing systems. We demonstrate that behavioural and evolutionary volatility caused by indirect interactions of goal-rational agents can be reduced by designing agents in a more socially-sensitive manner. We therefore challenge the assumption that designers of intelligent systems typically make, that goal-rationality is sufficient for achieving goals in shared environments

More Than Machines?

We know that robots are just machines. Why then do we often talk about them as if they were alive? Laura Voss explores this fascinating phenomenon, providing a rich insight into practices of animacy (and inanimacy) attribution to robot technology: from science-fiction to robotics R&D, from science communication to media discourse, and from the theoretical perspectives of STS to the cognitive sciences. Taking an interdisciplinary perspective, and backed by a wealth of empirical material, Voss shows how scientists, engineers, journalists - and everyone else - can face the challenge of robot technology appearing »a little bit alive« with a reflexive and yet pragmatic stance

More Than Machines? The Attribution of (In)Animacy to Robot Technology

We know that robots are just machines. Why then do we often talk about them as if they were alive? The author explores this fascinating phenomenon, providing a rich insight into practices of animacy (and inanimacy) attribution to robot technology: from science-fiction to robotics R&D, from science communication to media discourse, and from the theoretical perspectives of STS to the cognitive sciences. Taking an interdisciplinary perspective, and backed by a wealth of empirical material, the author shows how scientists, engineers, journalists - and everyone else - can face the challenge of robot technology appearing "a little bit alive" with a reflexive and yet pragmatic stance

More Than Machines?

We know that robots are just machines. Why then do we often talk about them as if they were alive? Laura Voss explores this fascinating phenomenon, providing a rich insight into practices of animacy (and inanimacy) attribution to robot technology: from science-fiction to robotics R&D, from science communication to media discourse, and from the theoretical perspectives of STS to the cognitive sciences. Taking an interdisciplinary perspective, and backed by a wealth of empirical material, Voss shows how scientists, engineers, journalists - and everyone else - can face the challenge of robot technology appearing »a little bit alive« with a reflexive and yet pragmatic stance

Multi-agent Learning For Game-theoretical Problems

Multi-agent systems are prevalent in the real world in various domains. In many multi-agent systems, interaction among agents is inevitable, and cooperation in some form is needed among agents to deal with the task at hand. We model the type of multi-agent systems where autonomous agents inhabit an environment with no global control or global knowledge, decentralized in the true sense. In particular, we consider game-theoretical problems such as the hedonic coalition formation games, matching problems, and Cournot games. We propose novel decentralized learning and multi-agent reinforcement learning approaches to train agents in learning behaviors and adapting to the environments. We use game-theoretic evaluation criteria such as optimality, stability, and resulting equilibria