Danny Weyns – författare

A concise and practical introduction to the foundations and engineering principles of self-adaptationThough it has recently gained significant momentum, the topic of self-adaptation remains largely under-addressed in academic and technical literature. This book changes that. Using a systematic and holistic approach, An Introduction to Self-adaptive Systems: A Contemporary Software Engineering Perspective provides readers with an accessible set of basic principles, engineering foundations, and applications of self-adaptation in software-intensive systems.It places self-adaptation in the context of techniques like uncertainty management, feedback control, online reasoning, and machine learning while acknowledging the growing consensus in the software engineering community that self-adaptation will be a crucial enabling feature in tackling the challenges of new, emerging, and future systems.The author combines cutting-edge technical research with basic principles and real-world insights to create a practical and strategically effective guide to self-adaptation. He includes features such as: An analysis of the foundational engineering principles and applications of self-adaptation in different domains, including the Internet-of-Things, cloud computing, and cyber-physical systemsEnd-of-chapter exercises at four different levels of complexity and difficultyAn accompanying author-hosted website with slides, selected exercises and solutions, models, and codePerfect for researchers, students, teachers, industry leaders, and practitioners in fields that directly or peripherally involve software engineering, as well as those in academia involved in a class on self-adaptivity, this book belongs on the shelves of anyone with an interest in the future of software and its engineering.

Methodological Guidelines for Modeling and Developing MAS-Based SimulationsThe intersection of agents, modeling, simulation, and application domains has been the subject of active research for over two decades. Although agents and simulation have been used effectively in a variety of application domains, much of the supporting research remains scattered in the literature, too often leaving scientists to develop multi-agent system (MAS) models and simulations from scratch. Multi-Agent Systems: Simulation and Applications provides an overdue review of the wide ranging facets of MAS simulation, including methodological and application-oriented guidelines. This comprehensive resource reviews two decades of research in the intersection of MAS, simulation, and different application domains. It provides scientists and developers with disciplined engineering approaches to modeling and developing MAS-based simulations. After providing an overview of the field’s history and its basic principles, as well as cataloging the various simulation engines for MAS, the book devotes three sections to current and emerging approaches and applications.Simulation for MAS — explains simulation support for agent decision making, the use of simulation for the design of self-organizing systems, the role of software architecture in simulating MAS, and the use of simulation for studying learning and stigmergic interaction.MAS for Simulation — discusses an agent-based framework for symbiotic simulation, the use of country databases and expert systems for agent-based modeling of social systems, crowd-behavior modeling, agent-based modeling and simulation of adult stem cells, and agents for traffic simulation. Tools — presents a number of representative platforms and tools for MAS and simulation, including Jason, James II, SeSAm, and RoboCup Rescue.Complete with over 200 figures and formulas, this reference book provides the necessary overview of experiences with MAS simulation and the tools needed to exploit simulation in MAS for future research in a vast array of applications including home security, computational systems biology, and traffic management.

This book constitutes the revised and selected papers from the 6th International Workshop on Engineering Multi-Agent Systems held in Stockholm, Sweden, in July 2018, in conjunction with AAMAS 2018.

This book constitutes the refereed proceedings of the tracks and workshops which complemented the 14th European Conference on Software Architecture, ECSA 2020, held in L'Aquila, Italy*, in September 2020. FAACS-MDE4SA - Joint Workshop on Formal Approaches for Advanced Computing Systems and Model-Driven Engineering for Software Architecture;

This book constitutes the refereed proceedings of the 15th International Conference on Software Architecture, ECSA 2021, held in Sweden, in September 2021.

This book constitutes the refereed proceedings of the tracks and workshops which complemented the 15th European Conference on Software Architecture, ECSA 2021, held in Växjö, Sweden*, in September 2021. MSR4SA - 1st International Workshop on Mining Software Repositories for Software Architecture;

This book constitutes the refereed proceedings of the tracks and workshops which complemented the 17th European Conference on Software Architecture, ECSA 2023, held in Istanbul, Turkey, in September 2023. The 29 full papers included in this book were carefully reviewed and selected from 32 submissions. DE Industry Track;

The 12 full papers and 15 short papers presented together with three education and training papers in this volume were carefully reviewed and selected from 100 submissions.

This book constitutes the thoroughly refereedpost-workshop proceedings of the 4th International Workshop on Environments forMultiagent Systems, E4MAS 2014 - 10 years later, held in Paris, France, in May2014 as an associated event of AAMAS 2014, the 13th International Conference onAutonomous Agents and Multiagent Systems.The 6 revised full papers presented together with 1roadmap paper and 7 invited papers were carefully reviewed and selected from 14initial submissions. The papers are organized in topical sections on connectingagents, environments, and humans; environments for complex and stigmergicsystems; virtual and simulated environments; and open agent environments andinteroperability.

The modern ?eld of multiagent systems has developed from two main lines of earlier research. Its practitioners generally regard it as a form of arti?cial intelligence (AI). Some of its earliest work was reported in a series of workshops in the US dating from1980,revealinglyentitled,“DistributedArti?cialIntelligence,”andpioneers often quoted a statement attributed to Nils Nilsson that “all AI is distributed. ” The locus of classical AI was what happens in the head of a single agent, and much MAS research re?ects this heritage with its emphasis on detailed modeling of the mental state and processes of individual agents. From this perspective, intelligenceisultimatelythepurviewofasinglemind,thoughitcanbeampli?ed by appropriate interactions with other minds. These interactions are typically mediated by structured protocols of various sorts, modeled on human conver- tional behavior. But the modern ?eld of MAS was not born of a single parent. A few - searchershavepersistentlyadvocatedideasfromthe?eldofarti?ciallife(ALife). These scientists were impressed by the complex adaptive behaviors of commu- ties of animals (often extremely simple animals, such as insects or even micro- ganisms). The computational models on which they drew were often created by biologists who used them not to solve practical engineering problems but to test their hypotheses about the mechanisms used by natural systems. In the ar- ?cial life model, intelligence need not reside in a single agent, but emerges at the level of the community from the nonlinear interactions among agents. - cause the individual agents are often subcognitive, their interactions cannot be modeled by protocols that presume linguistic competence.

This book constitutes the thoroughly refereed post-proceedings of the Second International Workshop on Environments for Multiagent Systems, E4MAS 2005, held in July 2005. The 16 revised papers presented were carefully reviewed and selected from the lectures given at the workshop. The papers are organized in topical sections on models, architecture, and design, mediated coordination, as well as applications.

This book constitutes the thoroughly refereed post-proceedings of the Third International Workshop on Environments for Multiagent Systems, E4MAS 2006, held in Hakodate, Japan in May 2006. The 15 revised papers in this volume are organized in topical sections on models, architecture, and design, mediated interaction and stigmery, governing environment, and applications.

Software intensive systems are increasingly expected to deal with changing user needs and dynamic operating conditions at run time. Examples are the need for life recon?gurations, management of resource variability, and dealing with p- ticular failure modes. Endowing systems with these kinds of capabilities poses severe challenges to software engineers and necessitates the development of new techniques, practices, and tools that build upon sound engineering principles. The ?eld of multi-agent systems focuses on the foundations and engineering of systems that consists of a network of autonomous entities (agents) that int- act to achieve the system goals. One line of research in multi-agent systems, inspired by biological, physical and other naturally occurring systems, concerns multi-agent systems in which agents share information and coordinate their - havior througha shared medium called an agentenvironment. Typical examples are gradient ?elds and digital pheromones that guide agents in their local c- text and as such facilitate the coordination of a community of agents. Since environment-mediation in multi-agent systems has shown to result in mana- able solutions with very adaptable qualities, it is a promising paradigm to deal with the increasing complexity and dynamism of distributed applications. Control in environment-mediated multi-agent systems is decentralized, i. e. , noneofthecomponentshasfullaccessorcontroloverthesystem. Self-organization isanapproachtoengineerdecentralized,distributedandresource-limitedsystems thatarecapableofdynamicallyadaptingtochangingconditionsandrequirements without external intervention. This useful system property is often re?ected in functionssuchasself-con?guration,self-optimization,andself-healing. Engine- ing approachesto self-organizing systems often rely on global functionality to emerge from localand autonomous decisions of individual agents that commu- catethroughasharedagentenvironment.

Multi-agent systems are claimed to be especially suited to the development of software systems that are decentralized, can deal flexibly with dynamic conditions, and are open to system components that come and go. This is why they are used in domains such as manufacturing control, automated vehicles, and e-commerce markets.Danny Weyns' book is organized according to the postulate that "developing multi-agent systems is 95% software engineering and 5% multi-agent systems theory." He presents a software engineering approach for multi-agent systems that is heavily based on software architecture - with, for example, tailored patterns such as "situated agent", "virtual environment", and "selective perception" - and on middleware for distributed coordination – with programming abstractions such as "views" and "roles." Next he shows the feasibility and applicability of this approach with the development of an automated transportation system consisting of a number of automatic guided vehicles transporting loads in an industrial setting.Weyns puts the development of multi-agent systems into a larger perspective with traditional software engineering approaches. With this, he opens up opportunities to exploit the body of knowledge developed in the multi-agent systems community to tackle some of the difficult challenges of modern-day software systems, such as decentralized control, location-awareness, self-adaption, and large-scale. Thus his book is of interest for both researchers and industrial software engineers who develop applications in areas such as distributed control systems and mobile applications where such requirements are of crucial importance.

Self-adaptability has been proposed as an e?ective approach to automate the complexity associated with the management of modern-day software systems. Self-adaptability endows a software system with the capability to adapt itself at runtime to deal with changing operating conditions or user requirements. Researchersinself-adaptivesystemsmostlytakeanarchitecture-centricfocus on developing top-down solutions. In this approach, the system is monitored to maintain an explicit (architectural) representation of the system and based on a set of (possibly dynamic) goals, the system's structure or behavior is adapted. Researchersofself-organizingsystemsmostlytakeanalgorithmic/organizational focus on developing bottom-up solutions. In this approach, the system com- nentsadapttheir localbehaviororpatternsofinteractiontochangingconditions and cooperatively realize system adaptation. Self-organizing approaches are - ten inspired by biological or natural phenomena. With the term "self-organizing architectures" (SOAR) we refer to an engineering approachfor self-adaptive s- tems that combinesarchitecturalapproachesforself-adaptability withprinciples and techniques from self-organization.Whereas both lines of research have been successful at alleviating some of the associated challenges of constructing self-adaptive systems, persistent ch- lenges remain, in particular for building complex distributed self-adaptive s- tems. Among the hard challenges in the architectural-centric approach are h- dling uncertainty and providing decentralized scalable solutions. Some of the hard challenges in the self-organizing approach are connecting local interactions with global system behavior, and accommodating a disciplined engineering - proach. The awarenessgrows that for building complex distributed self-adaptive systems, principles from both self-adaptive systems and self-organizing systems have to be combined.

Since the mid 1980s, software agents and multi-agent systems have grown into a very active area of research and also commercial development activity. One of the limiting factors in industry take-up of agent-technology,  however, is the lack of adequate software engineering support. The Agent-Oriented Software Engineering Workshop, AOSE, focuses on the synergies and cross fertilization between software engineering and agent research.This volume presents both thoroughly revised selected papers from the AOSE 2010 workshop held at AAMAS 2010 in Toronto, Canada in May 2010 as well as invited articles by leading researchers in the field. The papers cover a broad range of topics related to software engineering and agent-based systems, with particular attention to the integration of concepts and techniques from multi-agent systems with conventional engineering approaches on the one hand, and to the integration of agent-oriented software engineering and methodologies with conventional engineering processes on the other hand.

This book constitutes the thoroughly refereed post-workshop proceedings of 5 workshops, held at the 10th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2011, in Taipei, Taiwan, May 2-6, 2011. The 37 revised full papers presented together with 1 invited paper were carefully reviewed and selected from numerous submissions. The papers are organized in sections on the workshops Agent-Based Modeling for Policy Engineering (AMPLE), Agent-Oriented Software Engineering (AOSE), Autonomous Robots and Multirobot Systems (ARMS), Data Oriented Constructive Mining and Multi-Agent Simulation, Massively Multi-Agent Systems: Models, Methods and Tools (DOCM³AS), and Infrastructures and Tools for Multiagent Systems (ITMAS).