Hybrid Cloud Model Checking Using the Interaction Layer of HARMS for Ambient Intelligent Systems

Soon, humans will be co-living and taking advantage of the help of multi-agent systems in a broader way than the present. Such systems will involve machines or devices of any variety, including robots. These kind of solutions will adapt to the special needs of each individual. However, to the concern of this research effort, systems like the ones mentioned above might encounter situations that will not be seen before execution time. It is understood that there are two possible outcomes that could materialize; either keep working without corrective measures, which could lead to an entirely different end or completely stop working. Both results should be avoided, specially in cases where the end user will depend on a high level guidance provided by the system, such as in ambient intelligence applications. This dissertation worked towards two specific goals. First, to assure that the system will always work, independently of which of the agents performs the different tasks needed to accomplish a bigger objective. Second, to provide initial steps towards autonomous survivable systems which can change their future actions in order to achieve the original final goals. Therefore, the use of the third layer of the HARMS model was proposed to insure the indistinguishability of the actors accomplishing each task and sub-task without regard of the intrinsic complexity of the activity. Additionally, a framework was proposed using model checking methodology during run-time for providing possible solutions to issues encountered in execution time, as a part of the survivability feature of the systems final goals

Securing communication within the harms model for use with firefighting robots

Humans and robots must work together in increasingly complex networks to achieve a common goal. In this research, firefighting robots are a part of a larger, decentralized system of humans, agents, robots, machines, and sensors (HARMS). Although communication in a HARMS model has been utilized in previous research, this new study looks at the security considerations of the communications layer of the HARMS model. A network attack known as a man-in-the-middle attack is successfully demonstrated in this paper. Then, a secure communications protocol is proposed to help provide confidentiality and authentication of HARMS actors. This research is applied to any system that utilizes a HARMS network, including firefighting robots, to help ensure malicious entities cannot exploit communications by system actors. Instead, system actors that confirm their identity can communicate securely in a decentralized way for indistinguishable task completion. The results of this experiment are successful, indicating that secure communication can prevent man-in-the-middle attacks with minor differences in operation

Integrated intelligent systems for industrial automation: the challenges of Industry 4.0, information granulation and understanding agents .

The objective of the paper consists in considering the challenges of new automation paradigm Industry 4.0 and reviewing the-state-of-the-art in the field of its enabling information and communication technologies, including Cyberphysical Systems, Cloud Computing, Internet of Things and Big Data. Some ways of multi-dimensional, multi-faceted industrial Big Data representation and analysis are suggested. The fundamentals of Big Data processing with using Granular Computing techniques have been developed. The problem of constructing special cognitive tools to build artificial understanding agents for Integrated Intelligent Enterprises has been faced

Organizational Posthumanism

Building on existing forms of critical, cultural, biopolitical, and sociopolitical posthumanism, in this text a new framework is developed for understanding and guiding the forces of technologization and posthumanization that are reshaping contemporary organizations. This ‘organizational posthumanism’ is an approach to analyzing, creating, and managing organizations that employs a post-dualistic and post-anthropocentric perspective and which recognizes that emerging technologies will increasingly transform the kinds of members, structures, systems, processes, physical and virtual spaces, and external ecosystems that are available for organizations to utilize. It is argued that this posthumanizing technologization of organizations will especially be driven by developments in three areas: 1) technologies for human augmentation and enhancement, including many forms of neuroprosthetics and genetic engineering; 2) technologies for synthetic agency, including robotics, artificial intelligence, and artificial life; and 3) technologies for digital-physical ecosystems and networks that create the environments within which and infrastructure through which human and artificial agents will interact. Drawing on a typology of contemporary posthumanism, organizational posthumanism is shown to be a hybrid form of posthumanism that combines both analytic, synthetic, theoretical, and practical elements. Like analytic forms of posthumanism, organizational posthumanism recognizes the extent to which posthumanization has already transformed businesses and other organizations; it thus occupies itself with understanding organizations as they exist today and developing strategies and best practices for responding to the forces of posthumanization. On the other hand, like synthetic forms of posthumanism, organizational posthumanism anticipates the fact that intensifying and accelerating processes of posthumanization will create future realities quite different from those seen today; it thus attempts to develop conceptual schemas to account for such potential developments, both as a means of expanding our theoretical knowledge of organizations and of enhancing the ability of contemporary organizational stakeholders to conduct strategic planning for a radically posthumanized long-term future

Consortium for Robotics and Unmanned Systems Education and Research (CRUSER) 2019 Annual Report

Prepared for: Dr. Brian Bingham, CRUSER DirectorThe Naval Postgraduate School (NPS) Consortium for Robotics and Unmanned Systems Education and Research (CRUSER) provides a collaborative environment and community of interest for the advancement of unmanned systems (UxS) education and research endeavors across the Navy (USN), Marine Corps (USMC) and Department of Defense (DoD). CRUSER is a Secretary of the Navy (SECNAV) initiative to build an inclusive community of interest on the application of unmanned systems (UxS) in military and naval operations. This 2019 annual report summarizes CRUSER activities in its eighth year of operations and highlights future plans.Deputy Undersecretary of the Navy PPOIOffice of Naval Research (ONR)Approved for public release; distribution is unlimited

Consortium for Robotics and Unmanned Systems Education and Research (CRUSER) 2019 Annual Report

Prepared for: Dr. Brian Bingham, CRUSER DirectorThe Naval Postgraduate School (NPS) Consortium for Robotics and Unmanned Systems Education and Research (CRUSER) provides a collaborative environment and community of interest for the advancement of unmanned systems (UxS) education and research endeavors across the Navy (USN), Marine Corps (USMC) and Department of Defense (DoD). CRUSER is a Secretary of the Navy (SECNAV) initiative to build an inclusive community of interest on the application of unmanned systems (UxS) in military and naval operations. This 2019 annual report summarizes CRUSER activities in its eighth year of operations and highlights future plans.Deputy Undersecretary of the Navy PPOIOffice of Naval Research (ONR)Approved for public release; distribution is unlimited

Formal methods for analysing, coordinating, and controlling decisions in multi-agent systems

Multiagentensysteme sind verteilte (Computer)Systeme, die sich aus autonomen interagierenden Systemkomponenten, bezeichnet als Agenten, zusammensetzen. Sie bieten ein flexibles Framework zur Modellierung und Analyse von interaktiven Systemen, in denen Kooperation, Eigeninteresse und Autonomie eine entscheidende Rolle spielen. Dies ist zum Beispiel der Fall in Smart Grids. Eine Herausforderung in solchen Systemen ist die Kontrolle und die Koordination von Systemausführungen. Agenten handeln autonom und lassen sich daher oftmals nicht direkt kontrollieren, sondern bestenfalls beeinflussen. Aufgrund der Autonomie und des Selbstinteresses, ist es schwierig, angemessene Kontrollmechanismen zu finden. Die vorliegende Arbeit behandelt formale Grundlagen zu den Themen Entscheidungsfindung, Koordination und Kontrolle in Multiagentensystemen. Insbesondere werden in diesem Zusammenhang Logiken zur Analyse und Spezifikation von strategischen Fähigkeiten von Agenten, unter diversen Restriktionen, untersucht. Es werden formale Ansätze zur Beeinflussung und Überwachung von Systemausführungen eingeführt. In einem weiteren Teil der Arbeit wird mittels spieltheoretischer Verfahren analysiert, wie rationale Agenten interagieren und Entscheidungen treffen. Es wird argumentiert, dass formale Methoden und Werkzeuge zur Analyse und Kontrolle von autonomen Systemen entscheidend für deren verlässliche Entwicklung sind.Multi-agent systems (MASs) are distributed (computer) systems composed of autonomously (inter-)acting system components referred to as agents. MASs offer a flexible framework to model and analyse many real world settings in which cooperation, self-interest, and autonomy are crucial elements. A key challenge in such settings is the control and coordination of behavior. However, due to the agents' autonomy behavior can often not be controlled, but at best be influenced in some way or another. For example, agents can be given incentives in order to affect their decision-making in such a way that the emergent behavior of all actors is desirable from the system's perspective. The properties of self-interest and autonomy make it challenging to find appropriate control mechanisms. Existing coordination and control approaches from the distributed system literature are often not applicable due to the lack of direct control on the system components of MASs. New methods and tools are needed. In this thesis formal foundations related to the subjects of decision making, coordination and control in MASs are studied. In particular, we investigate (extensions of) temporal and strategic logics which capture specific capabilities of agents that influence their decision making. We also propose formal approaches to control, coordinate and monitor the emergent behavior in MASs. In the last part of the thesis we analyse how rational agents interact and make decisions using game theoretical methods. We argue that such formal approaches and tools to analyse and control autonomous systems are crucial for the development of reliable and flexible systems and will become even more crucial in the near future

A federated learning framework for the next-generation machine learning systems

Dissertação de mestrado em Engenharia Eletrónica Industrial e Computadores (especialização em Sistemas Embebidos e Computadores)The end of Moore's Law aligned with rising concerns about data privacy is forcing machine learning (ML) to shift from the cloud to the deep edge, near to the data source. In the next-generation ML systems, the inference and part of the training process will be performed right on the edge, while the cloud will be responsible for major ML model updates. This new computing paradigm, referred to by academia and industry researchers as federated learning, alleviates the cloud and network infrastructure while increasing data privacy. Recent advances have made it possible to efficiently execute the inference pass of quantized artificial neural networks on Arm Cortex-M and RISC-V (RV32IMCXpulp) microcontroller units (MCUs). Nevertheless, the training is still confined to the cloud, imposing the transaction of high volumes of private data over a network. To tackle this issue, this MSc thesis makes the first attempt to run a decentralized training in Arm Cortex-M MCUs. To port part of the training process to the deep edge is proposed L-SGD, a lightweight version of the stochastic gradient descent optimized for maximum speed and minimal memory footprint on Arm Cortex-M MCUs. The L-SGD is 16.35x faster than the TensorFlow solution while registering a memory footprint reduction of 13.72%. This comes at the cost of a negligible accuracy drop of only 0.12%. To merge local model updates returned by edge devices this MSc thesis proposes R-FedAvg, an implementation of the FedAvg algorithm that reduces the impact of faulty model updates returned by malicious devices.O fim da Lei de Moore aliado às crescentes preocupações sobre a privacidade dos dados gerou a necessidade de migrar as aplicações de Machine Learning (ML) da cloud para o edge, perto da fonte de dados. Na próxima geração de sistemas ML, a inferência e parte do processo de treino será realizada diretamente no edge, enquanto que a cloud será responsável pelas principais atualizações do modelo ML. Este novo paradigma informático, referido pelos investigadores académicos e industriais como treino federativo, diminui a sobrecarga na cloud e na infraestrutura de rede, ao mesmo tempo que aumenta a privacidade dos dados. Avanços recentes tornaram possível a execução eficiente do processo de inferência de redes neurais artificiais quantificadas em microcontroladores Arm Cortex-M e RISC-V (RV32IMCXpulp). No entanto, o processo de treino continua confinado à cloud, impondo a transação de grandes volumes de dados privados sobre uma rede. Para abordar esta questão, esta dissertação faz a primeira tentativa de realizar um treino descentralizado em microcontroladores Arm Cortex-M. Para migrar parte do processo de treino para o edge é proposto o L-SGD, uma versão lightweight do tradicional método stochastic gradient descent (SGD), otimizada para uma redução de latência do processo de treino e uma redução de recursos de memória nos microcontroladores Arm Cortex-M. O L-SGD é 16,35x mais rápido do que a solução disponibilizada pelo TensorFlow, ao mesmo tempo que regista uma redução de utilização de memória de 13,72%. O custo desta abordagem é desprezível, sendo a perda de accuracy do modelo de apenas 0,12%. Para fundir atualizações de modelos locais devolvidas por dispositivos do edge, é proposto o RFedAvg, uma implementação do algoritmo FedAvg que reduz o impacto de atualizações de modelos não contributivos devolvidos por dispositivos maliciosos

Digital Humanism

This open access book deals with cultural and philosophical aspects of artificial intelligence (AI) and pleads for a “digital humanism”. This term is beginning to be en vogue everywhere. Due to a growing discontentment with the way digitalization is being used in the world, particularly formulated by former heroes of Internet, social media and search engine companies, philosophical as well as industrial thought leaders begin to plead for a humane use of digital tools. Yet the term “digital humanism” is a particular terminology that lacks a sound conceptual and philosophical basis and needs clarification still – and this gap is exactly filled by this book. It propagates a vision of society in which digitization is used to strengthen human self-determination, autonomy and dignity and whose time has come to be propagated throughout the world. The advantage of this book is that it is philosophically sound and yet written in a way that will make it accessible for everybody interested in the subject. Every chapters begins with a film scene illustrating a precise philosophical problem with AI and how we look at it – making the book not only readable, but even entertaining. And after having read the book the reader will have a clear vision of what it means to live in a world where digitization and AI are central technologies for a better and more humane civilization