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Model Checking and Artificial Intelligence: 6th International Workshop, MoChArt 2010, Atlanta, GA, USA, July 11, 2010, Revised Selected and Invited Papers (Lecture Notes in Computer Science #6572)

This book presents revised versions of selected papers from the 6th Workshop on Model Checking and Artificial Intelligence, MoChArt 2010, held in Atlanta, GA, USA in July 2010, as well as papers contributed subsequent to the workshop. The 7 papers presented were carefully reviewed and selected for inclusion in this book. In addition, the book also contains an extended abstract of the invited talk held at the workshop. The topics covered by these papers are general search algorithms, application of AI techniques to automated program verification, multiagent systems and epistemic logic, abstraction, epistemic model checking, and theory of model checking.

Model Checking and Artificial Intelligence: 5th International Workshop, MoChArt 2008, Patras, Greece, July 21, 2008, Revised Selected and Invited Papers (Lecture Notes in Computer Science #5348)

This book constitutes the thoroughly refereed post-workshop proceedings of the 5th Workshop on Model Checking and Artificial Intelligence, MOCHART 2008, held in Patras, Greece, in July 2008 as a satellite event of ECAI 2008, the 18th biannual European conference on Artificial Intelligence. The 9 revised full workshop papers presented together with 2 invited lectures have gone through two rounds of reviewing and improvement and were carefully selected for inclusion in the book. The workshop covers all ideas, research, experiments and tools that relate to both MC and AI fields.

Model-Based Testing of Reactive Systems: Advanced Lectures (Lecture Notes in Computer Science #3472)

Testing is the primary hardware and software verification technique used by industry today. Usually, it is ad hoc, error prone, and very expensive. In recent years, however, many attempts have been made to develop more sophisticated formal testing methods. This coherent book provides an in-depth assessment of this emerging field, focusing on formal testing of reactive systems. This book is based on a seminar held in Dagstuhl Castle, Germany, in January 2004. It presents 19 carefully reviewed and revised lectures given at the seminar in a well-balanced way ensuring competent complementary coverage of all relevant aspects. An appendix provides a glossary for model-based testing and basics on finite state machines and on labelled transition systems. The lectures are presented in topical sections on testing of finite state machines, testing of labelled transition systems, model-based test case generation, tools and case studies, standardized test notation and execution architectures, and beyond testing.

Model-Based Testing Essentials - Guide to the ISTQB Certified Model-Based Tester: Foundation Level

Provides a practical and comprehensive introduction to the key aspects of model-based testing as taught in the ISTQB® Model-Based Tester—Foundation Level Certification Syllabus This book covers the essentials of Model-Based Testing (MBT) needed to pass the ISTQB® Foundation Level Model-Based Tester Certification. The text begins with an introduction to MBT, covering both the benefits and the limitations of MBT. The authors review the various approaches to model-based testing, explaining the fundamental processes in MBT, the different modeling languages used, common good modeling practices, and the typical mistakes and pitfalls. The book explains the specifics of MBT test implementation, the dependencies on modeling and test generation activities, and the steps required to automate the generated test cases. The text discusses the introduction of MBT in a company, presenting metrics to measure success and good practices to apply. Provides case studies illustrating different approaches to Model-Based Testing Includes in-text exercises to encourage readers to practice modeling and test generation activities Contains appendices with solutions to the in-text exercises, a short quiz to test readers, along with additional information Model-Based Testing Essentials – Guide to the ISTQB® Certified Model-Based Tester – Foundation Level is written primarily for participants of the ISTQB® Certification: software engineers, test engineers, software developers, and anybody else involved in software quality assurance. This book can also be used for anyone who wants a deeper understanding of software testing and of the use of models for test generation.

Model-Based Testing Essentials - Guide to the ISTQB Certified Model-Based Tester: Foundation Level

Provides a practical and comprehensive introduction to the key aspects of model-based testing as taught in the ISTQB® Model-Based Tester—Foundation Level Certification Syllabus This book covers the essentials of Model-Based Testing (MBT) needed to pass the ISTQB® Foundation Level Model-Based Tester Certification. The text begins with an introduction to MBT, covering both the benefits and the limitations of MBT. The authors review the various approaches to model-based testing, explaining the fundamental processes in MBT, the different modeling languages used, common good modeling practices, and the typical mistakes and pitfalls. The book explains the specifics of MBT test implementation, the dependencies on modeling and test generation activities, and the steps required to automate the generated test cases. The text discusses the introduction of MBT in a company, presenting metrics to measure success and good practices to apply. Provides case studies illustrating different approaches to Model-Based Testing Includes in-text exercises to encourage readers to practice modeling and test generation activities Contains appendices with solutions to the in-text exercises, a short quiz to test readers, along with additional information Model-Based Testing Essentials – Guide to the ISTQB® Certified Model-Based Tester – Foundation Level is written primarily for participants of the ISTQB® Certification: software engineers, test engineers, software developers, and anybody else involved in software quality assurance. This book can also be used for anyone who wants a deeper understanding of software testing and of the use of models for test generation.

Model-Based Systems Engineering with OPM and SysML

Model-Based Systems Engineering (MBSE), which tackles architecting and design of complex systems through the use of formal models, is emerging as the most critical component of systems engineering. This textbook specifies the two leading conceptual modeling languages, OPM—the new ISO 19450, composed primarily by the author of this book, and OMG SysML. It provides essential insights into a domain-independent, discipline-crossing methodology of developing or researching complex systems of any conceivable kind and size. Combining theory with a host of industrial, biological, and daily life examples, the book explains principles and provides guidelines for architecting complex, multidisciplinary systems, making it an indispensable resource for systems architects and designers, engineers of any discipline, executives at all levels, project managers, IT professional, systems scientists, and engineering students.

Model-based Systems Architecting: Using CESAM to Architect Complex Systems (pdf)

Model-based Systems Architecting: Using CESAM to Architect Complex Systems

Model-based Systems Architecting is a key tool for designing complex industrial systems. It is dedicated to the working systems architects, engineers and modelers, in order to help them master the complex integrated systems that they are dealing with in their day-to-day professional lives. It presents the CESAMES Systems Architecting Method (CESAM), a systems architecting and modeling framework which has been developed since 2003 in close interaction with many leading industrial companies, providing rigorous and unambiguous semantics for all classical systems architecture concepts. This approach is practically robust and easy-to-use: during the last decade, it was deployed in more than 2,000 real system development projects within the industry, and distributed to around 10,000 engineers around the globe.

Model-Based System Architecture (Wiley Series in Systems Engineering and Management)

Presents modeling approaches that can be performed in SysML and other modeling languages This book combines the emerging discipline of systems architecting with model-based approaches using SysML. The early chapters of the book provide the fundamentals of systems architecting; discussing what systems architecting entails and how it benefits systems engineering. Model-based systems engineering is then defined, and its capabilities to develop complex systems on time and in a feasible quality are discussed. The remainder of the book covers important topics such as: architecture descriptions; architecture patterns; perspectives, viewpoints, views and their relation to system architecture; the roles of a system architect, their team, and stakeholders; systems architecting processes; agile approaches to systems architecting; variant modeling techniques; architecture frameworks; and architecture assessment. The book's organization allows experts to read the chapters out of sequence. Novices can read the chapters sequentially to gain a systematic introduction to system architecting. Model-Based System Architecture: Provides comprehensive coverage of the Functional Architecture for Systems (FAS) method created by the authors and based on common MBSE practices Covers architecture frameworks, including the System of Systems, Zachman Frameworks, TOGAF®, and more Includes a consistent example system, the “Virtual Museum Tour” system, that allows the authors to demonstrate the systems architecting concepts covered in the book Model-Based System Architecture is a comprehensive reference for system architects and systems engineers in technology companies. This book will also serve as a reference to students and researchers interested in functional architectures. Tim Weilkiens is the CEO at the German consultancy oose Innovative Informatik and co-author of the SysML specification. He has introduced model-based systems engineering to a variety of industry sectors. He is author of several books about modeling and the MBSE methodology SYSMOD. Jesko G. Lamm is a Senior Systems Engineer at Bernafon, a Swiss manufacturer for hearing instruments. With Tim Weilkiens, Jesko G. Lamm founded the Functional Architectures working group of the German chapter of INCOSE. Stephan Roth is a coach, consultant, and trainer for systems and software engineering at the German consultancy oose Innovative Informatik. He is a state-certified technical assistant for computer science from Physikalisch-Technische Lehranstalt (PTL) Wedel and a certified systems engineer (GfSE)®- Level C. Markus Walker works at Schindler Elevator in the research and development division as elevator system architect. He is an INCOSE Certified Systems Engineering Professional (CSEP) and is engaged in the committee of the Swiss chapter of INCOSE.

Model-Based System Architecture (Wiley Series in Systems Engineering and Management)

Presents modeling approaches that can be performed in SysML and other modeling languages This book combines the emerging discipline of systems architecting with model-based approaches using SysML. The early chapters of the book provide the fundamentals of systems architecting; discussing what systems architecting entails and how it benefits systems engineering. Model-based systems engineering is then defined, and its capabilities to develop complex systems on time and in a feasible quality are discussed. The remainder of the book covers important topics such as: architecture descriptions; architecture patterns; perspectives, viewpoints, views and their relation to system architecture; the roles of a system architect, their team, and stakeholders; systems architecting processes; agile approaches to systems architecting; variant modeling techniques; architecture frameworks; and architecture assessment. The book's organization allows experts to read the chapters out of sequence. Novices can read the chapters sequentially to gain a systematic introduction to system architecting. Model-Based System Architecture: Provides comprehensive coverage of the Functional Architecture for Systems (FAS) method created by the authors and based on common MBSE practices Covers architecture frameworks, including the System of Systems, Zachman Frameworks, TOGAF®, and more Includes a consistent example system, the “Virtual Museum Tour” system, that allows the authors to demonstrate the systems architecting concepts covered in the book Model-Based System Architecture is a comprehensive reference for system architects and systems engineers in technology companies. This book will also serve as a reference to students and researchers interested in functional architectures. Tim Weilkiens is the CEO at the German consultancy oose Innovative Informatik and co-author of the SysML specification. He has introduced model-based systems engineering to a variety of industry sectors. He is author of several books about modeling and the MBSE methodology SYSMOD. Jesko G. Lamm is a Senior Systems Engineer at Bernafon, a Swiss manufacturer for hearing instruments. With Tim Weilkiens, Jesko G. Lamm founded the Functional Architectures working group of the German chapter of INCOSE. Stephan Roth is a coach, consultant, and trainer for systems and software engineering at the German consultancy oose Innovative Informatik. He is a state-certified technical assistant for computer science from Physikalisch-Technische Lehranstalt (PTL) Wedel and a certified systems engineer (GfSE)®- Level C. Markus Walker works at Schindler Elevator in the research and development division as elevator system architect. He is an INCOSE Certified Systems Engineering Professional (CSEP) and is engaged in the committee of the Swiss chapter of INCOSE.

Model-Based Software Performance Analysis

Poor performance is one of the main quality-related shortcomings that cause software projects to fail. Thus, the need to address performance concerns early during the software development process is fully acknowledged, and there is a growing interest in the research and software industry communities towards techniques, methods and tools that permit to manage system performance concerns as an integral part of software engineering. Model-based software performance analysis introduces performance concerns in the scope of software modeling, thus allowing the developer to carry on performance analysis throughout the software lifecycle. With this book, Cortellessa, Di Marco and Inverardi provide the cross-knowledge that allows developers to tackle software performance issues from the very early phases of software development. They explain the basic concepts of performance analysis and describe the most representative methodologies used to annotate and transform software models into performance models. To this end, they go all the way from performance primers through software and performance modeling notations to the latest transformation-based methodologies. As a result, their book is a self-contained reference text on software performance engineering, from which different target groups will benefit: professional software engineers and graduate students in software engineering will learn both basic concepts of performance modeling and new methodologies; while performance specialists will find out how to investigate software performance model building.

Model-Based Software and Data Integration: First International Workshop, MBSDI 2008, Berlin, Germany, April 1-3, 2008, Proceedings (Communications in Computer and Information Science #8)

Model-Based Safety and Assessment: 5th International Symposium, IMBSA 2017, Trento, Italy, September 11–13, 2017, Proceedings (Lecture Notes in Computer Science #10437)

​This book constitutes the proceedings of the 5th International Symposium on Model-Based Safety and Assessment, IMBSA 2017, held inTrento, Italy, in September 2017.The 17 revised full papers presented were carefully reviewed and selected from 29 initial submissions. The papers are organized in topical sections on safety process; safety models and languages; fault detection and propagation; safety assessment in the automotive domain; and case studies.

Model-Based Safety and Assessment: 4th International Symposium, IMBSA 2014, Munich, Germany, October 27-29, 2014, Proceedings (Lecture Notes in Computer Science #8822)

This book constitutes the refereed proceedings of the 4th International Symposium on Model-Based Safety and Assessment, IMBSA 2014, held in Munich, Germany, in October 2014. The 15 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on modeling paradigms, validation and testing, fault detection and handling, safety assessment in the automotive domain, and case studies.

Model-Based Safety and Assessment: 6th International Symposium, IMBSA 2019, Thessaloniki, Greece, October 16–18, 2019, Proceedings (Lecture Notes in Computer Science #11842)

This book constitutes the proceedings of the 6th International Symposium on Model-Based Safety and Assessment, IMBSA 2019, held inThessaloniki, Greece, in October 2019.The 24 revised full papers presented were carefully reviewed and selected from 46 initial submissions. The papers are organized in topical sections on safety models and languages; dependability analysis process; safety assessment; safety assessment in automotive industry; AI in safety assessment.

Model-Based Safety and Assessment: 8th International Symposium, IMBSA 2022, Munich, Germany, September 5–7, 2022, Proceedings (Lecture Notes in Computer Science #13525)

This book constitutes the proceedings of the 8th International Symposium on Model-Based Safety and Assessment, IMBSA 2022, held in Munich, Germany, in September 2022. The 15 revised full papers and 3 short papers presented were carefully reviewed and selected from 27 initial submissions. The papers focus on model-based and automated ways of assessing safety and other attributes of dependability of complex systems. They are organized in topical sections on safety analysis automation, MBSA practices, causal models and failure modeling strategies, designing mitigations of faults and attacks, data based safety analysis, dynamic risk assessment.

Model-Based Safety and Assessment: 7th International Symposium, IMBSA 2020, Lisbon, Portugal, September 14–16, 2020, Proceedings (Lecture Notes in Computer Science #12297)

This book constitutes the proceedings of the 7th International Symposium on Model-Based Safety and Assessment, IMBSA 2020, held in Lisbon, Portugal, in September 2020. The conference was held virtually due to the COVID-19 pandemic. The 15 revised full papers and 4 short papers presented were carefully reviewed and selected from 30 initial submissions. The papers are organized in topical sections on safety models and languages; state-space modeling; dependability analysis process; safety assessment in automotive domain; AI and safety assurance.

Model-Based Reinforcement Learning: From Data to Continuous Actions with a Python-based Toolbox (IEEE Press Series on Control Systems Theory and Applications)

Model-Based Reinforcement Learning Explore a comprehensive and practical approach to reinforcement learning Reinforcement learning is an essential paradigm of machine learning, wherein an intelligent agent performs actions that ensure optimal behavior from devices. While this paradigm of machine learning has gained tremendous success and popularity in recent years, previous scholarship has focused either on theory—optimal control and dynamic programming – or on algorithms—most of which are simulation-based. Model-Based Reinforcement Learning provides a model-based framework to bridge these two aspects, thereby creating a holistic treatment of the topic of model-based online learning control. In doing so, the authors seek to develop a model-based framework for data-driven control that bridges the topics of systems identification from data, model-based reinforcement learning, and optimal control, as well as the applications of each. This new technique for assessing classical results will allow for a more efficient reinforcement learning system. At its heart, this book is focused on providing an end-to-end framework—from design to application—of a more tractable model-based reinforcement learning technique. Model-Based Reinforcement Learning readers will also find: A useful textbook to use in graduate courses on data-driven and learning-based control that emphasizes modeling and control of dynamical systems from data Detailed comparisons of the impact of different techniques, such as basic linear quadratic controller, learning-based model predictive control, model-free reinforcement learning, and structured online learning Applications and case studies on ground vehicles with nonholonomic dynamics and another on quadrator helicopters An online, Python-based toolbox that accompanies the contents covered in the book, as well as the necessary code and data Model-Based Reinforcement Learning is a useful reference for senior undergraduate students, graduate students, research assistants, professors, process control engineers, and roboticists.

Model-Based Reinforcement Learning: From Data to Continuous Actions with a Python-based Toolbox (IEEE Press Series on Control Systems Theory and Applications)

Model-Based Reinforcement Learning Explore a comprehensive and practical approach to reinforcement learning Reinforcement learning is an essential paradigm of machine learning, wherein an intelligent agent performs actions that ensure optimal behavior from devices. While this paradigm of machine learning has gained tremendous success and popularity in recent years, previous scholarship has focused either on theory—optimal control and dynamic programming – or on algorithms—most of which are simulation-based. Model-Based Reinforcement Learning provides a model-based framework to bridge these two aspects, thereby creating a holistic treatment of the topic of model-based online learning control. In doing so, the authors seek to develop a model-based framework for data-driven control that bridges the topics of systems identification from data, model-based reinforcement learning, and optimal control, as well as the applications of each. This new technique for assessing classical results will allow for a more efficient reinforcement learning system. At its heart, this book is focused on providing an end-to-end framework—from design to application—of a more tractable model-based reinforcement learning technique. Model-Based Reinforcement Learning readers will also find: A useful textbook to use in graduate courses on data-driven and learning-based control that emphasizes modeling and control of dynamical systems from data Detailed comparisons of the impact of different techniques, such as basic linear quadratic controller, learning-based model predictive control, model-free reinforcement learning, and structured online learning Applications and case studies on ground vehicles with nonholonomic dynamics and another on quadrator helicopters An online, Python-based toolbox that accompanies the contents covered in the book, as well as the necessary code and data Model-Based Reinforcement Learning is a useful reference for senior undergraduate students, graduate students, research assistants, professors, process control engineers, and roboticists.

Model-Based Reasoning in Scientific Discovery

The volume is based on the papers that were presented at the Interna­ tional Conference Model-Based Reasoning in Scientific Discovery (MBR'98), held at the Collegio Ghislieri, University of Pavia, Pavia, Italy, in December 1998. The papers explore how scientific thinking uses models and explanatory reasoning to produce creative changes in theories and concepts. The study of diagnostic, visual, spatial, analogical, and temporal rea­ soning has demonstrated that there are many ways of performing intelligent and creative reasoning that cannot be described with the help only of tradi­ tional notions of reasoning such as classical logic. Traditional accounts of scientific reasoning have restricted the notion of reasoning primarily to de­ ductive and inductive arguments. Understanding the contribution of model­ ing practices to discovery and conceptual change in science requires ex­ panding scientific reasoning to include complex forms of creative reasoning that are not always successful and can lead to incorrect solutions. The study of these heuristic ways of reasoning is situated at the crossroads of philoso­ phy, artificial intelligence, cognitive psychology, and logic; that is, at the heart of cognitive science. There are several key ingredients common to the various forms of model­ based reasoning to be considered in this book. The models are intended as in­ terpretations of target physical systems, processes, phenomena, or situations. The models are retrieved or constructed on the basis of potentially satisfying salient constraints of the target domain.

Model-Based Reasoning in Science, Technology, and Medicine (Studies in Computational Intelligence #64)

The volume is based on papers presented at the international conference on Model-Based Reasoning in Science and Medicine held in China in 2006. The presentations explore how scientific thinking uses models and explanatory reasoning to produce creative changes in theories and concepts. The contributions to the book are written by researchers active in the area of creative reasoning in science and technology. They include the subject area’s most recent results and achievements.

Model-Based Reasoning in Science and Technology: Theoretical and Cognitive Issues (Studies in Applied Philosophy, Epistemology and Rational Ethics #8)

This book contains contributions presented during the international conference on Model-Based Reasoning (MBR´012), held on June 21-23 in Sestri Levante, Italy. Interdisciplinary researchers discuss in this volume how scientific cognition and other kinds of cognition make use of models, abduction, and explanatory reasoning in order to produce important or creative changes in theories and concepts. Some of the contributions analyzed the problem of model-based reasoning in technology and stressed the issues of scientific and technological innovation. The book is divided in three main parts: models, mental models, representations; abduction, problem solving and practical reasoning; historical, epistemological and technological issues. The volume is based on the papers that were presented at the international

Model-Based Reasoning in Science and Technology: Abduction, Logic, and Computational Discovery (Studies in Computational Intelligence #314)

Model-Based Reasoning in Science and Technology: Logical, Epistemological, and Cognitive Issues (Studies in Applied Philosophy, Epistemology and Rational Ethics #27)

This book discusses how scientific and other types of cognition make use of models, abduction, and explanatory reasoning in order to produce important or creative changes in theories and concepts. It includes revised contributions presented during the international conference on Model-Based Reasoning (MBR’015), held on June 25-27 in Sestri Levante, Italy. The book is divided into three main parts, the first of which focuses on models, reasoning and representation. It highlights key theoretical concepts from an applied perspective, addressing issues concerning information visualization, experimental methods and design. The second part goes a step further, examining abduction, problem solving and reasoning. The respective contributions analyze different types of reasoning, discussing various concepts of inference and creativity and their relationship with experimental data. In turn, the third part reports on a number of historical, epistemological and technological issues. By analyzing possible contradictions in modern research and describing representative case studies in experimental research, this part aims at fostering new discussions and stimulating new ideas. All in all, the book provides researchers and graduate students in the field of applied philosophy, epistemology, cognitive science and artificial intelligence alike with an authoritative snapshot of current theories and applications of model-based reasoning.

Model-Based Reasoning in Science and Technology: Inferential Models for Logic, Language, Cognition and Computation (Studies in Applied Philosophy, Epistemology and Rational Ethics #49)

This book discusses how scientific and other types of cognition make use of models, abduction, and explanatory reasoning in order to produce important and innovative changes in theories and concepts. Gathering revised contributions presented at the international conference on Model-Based Reasoning (MBR18), held on October 24–26 2018 in Seville, Spain, the book is divided into three main parts. The first focuses on models, reasoning, and representation. It highlights key theoretical concepts from an applied perspective, and addresses issues concerning information visualization, experimental methods, and design. The second part goes a step further, examining abduction, problem solving, and reasoning. The respective papers assess different types of reasoning, and discuss various concepts of inference and creativity and their relationship with experimental data. In turn, the third part reports on a number of epistemological and technological issues. By analyzing possible contradictions in modern research and describing representative case studies, this part is intended to foster new discussions and stimulate new ideas. All in all, the book provides researchers and graduate students in the fields of applied philosophy, epistemology, cognitive science, and artificial intelligence alike with an authoritative snapshot of the latest theories and applications of model-based reasoning.