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A concise and practical introduction to the foundations and engineering principles of self-adaptation Though 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 learni...
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 "selecti...
This book contains the refereed post-conference proceedings of the First International Self-Organizing Architectures Workshop (SOAR) in Cambridge, UK, in September 2009. The book includes 9 revised papers, which were selected from 17 submissions of the workshop, as well as 4 invited papers. The papers cover a broad range of topics related to self-organizing architectures, including self adaptive architectures, decentralized architectures, nature-inspired approaches, and learning approaches.
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.
Although tremendous progress has been made in Artificial Intelligence (AI), it entails new challenges. The growing complexity of learning tasks requires more complex AI components, which increasingly exhibit unreliable behaviour. In this book, we present a model-driven approach to model architectural safeguards for AI components and analyse their effect on the overall system reliability.
This book introduces major agent platforms, frameworks, systems, tools, and applications. Each system is described by their developers in sufficient detail so that the reader can get a good understanding of the architecture, functionality, and application areas of the system. All systems are running systems. One main focus of the book lies on agent platforms and toolkits.
This book contains the refereed post-conference proceedings of the First International Self-Organizing Architectures Workshop (SOAR) in Cambridge, UK, in September 2009. The book includes 9 revised papers, which were selected from 17 submissions of the workshop, as well as 4 invited papers. The papers cover a broad range of topics related to self-organizing architectures, including self adaptive architectures, decentralized architectures, nature-inspired approaches, and learning approaches.
Methodological Guidelines for Modeling and Developing MAS-Based Simulations The 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 tw...
Adaptive agents and multi-agent systems is an emerging and exciting interdisciplinary area of research and development involving artificial intelligence, software engineering, and developmental biology, as well as cognitive and social science. This book presents 17 revised and carefully reviewed papers taken from two workshops on the topic as well as 2 invited papers by leading researchers in the area. The papers deal with various aspects of machine learning, adaptation, and evolution in the context of agent systems and autonomous agents.
This book constitutes the refereed proceedings of the 15th International Conference on Software Architecture, ECSA 2021, held in Sweden, in September 2021. Due to the COVID-19 pandemic, the conference was held virtually. For the Research Track, 11 full papers, presented together with 5 short papers, were carefully reviewed and selected from 58 submissions. The papers are organized in topical sections as follows: architectures for reconfigurable and self-adaptive systems; machine learning for software architecture; architectural knowledge, decisions, and rationale; architecting for quality attributes; architecture-centric source code analysis; and experiences and learnings from industrial case studies.