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In this book, internationally recognized experts in philosophy of science, computer science, and modeling and simulation are contributing to the discussion on how ontology, epistemology, and teleology will contribute to enable the next generation of intelligent modeling and simulation applications. It is well understood that a simulation can provide the technical means to display the behavior of a system over time, including following observed trends to predict future possible states, but how reliable and trustworthy are such predictions? The questions about what we can know (ontology), how we gain new knowledge (epistemology), and what we do with this knowledge (teleology) are therefore illuminated from these very different perspectives, as each experts uses a different facet to look at these challenges. The result of bringing these perspectives into one book is a challenging compendium that gives room for a spectrum of challenges: from general philosophy questions, such as can we use modeling and simulation and other computational means at all to discover new knowledge, down to computational methods to improve semantic interoperability between systems or methods addressing how to apply the recent insights of service oriented approaches to support distributed artificial intelligence. As such, this book has been compiled as an entry point to new domains for students, scholars, and practitioners and to raise the curiosity in them to learn more to fully address the topics of ontology, epistemology, and teleology from philosophical, computational, and conceptual viewpoints.

Data structures (Computer science). --- Simulation methods -- Philosophy. --- Technology -- Philosophy. --- Engineering & Applied Sciences --- Computer Science --- Simulation methods --- Data structures (Computer science) --- Philosophy. --- Information structures (Computer science) --- Structures, Data (Computer science) --- Structures, Information (Computer science) --- Simulation techniques --- System simulation --- Engineering. --- Epistemology. --- Artificial intelligence. --- Computational intelligence. --- Computational Intelligence. --- Artificial Intelligence (incl. Robotics). --- Philosophy of Technology. --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Fifth generation computers --- Neural computers --- Mental philosophy --- Humanities --- Epistemology --- Theory of knowledge --- Philosophy --- Psychology --- Construction --- Industrial arts --- Technology --- File organization (Computer science) --- Abstract data types (Computer science) --- Operations research --- Systems engineering --- Models and modelmaking --- Genetic epistemology. --- Artificial Intelligence. --- Developmental psychology --- Knowledge, Theory of

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The International Council on Systems Engineering (INCOSE) defines Systems Engineering as an interdisciplinary approach and means to enable the realization of successful systems.   Researchers are using intelligence-based techniques to support the practices of systems engineering in an innovative way. This research volume includes a selection of contributions by subject experts to design better systems.

COMPUTERS -- Expert Systems. --- Expert systems (Computer science). --- Systems engineering. --- Engineering & Applied Sciences --- Computer Science --- Intelligent control systems. --- Engineering systems --- System engineering --- Intelligent control --- Intelligent controllers --- Design and construction --- Engineering. --- Artificial intelligence. --- Computational intelligence. --- Computational Intelligence. --- Artificial Intelligence (incl. Robotics). --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Construction --- Industrial arts --- Technology --- Automatic control --- Engineering --- Industrial engineering --- System analysis --- Artificial Intelligence.

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"This book presents a series of Human System Engineering (HSE) applications on a range of topics, such as interface design, training requirements, personnel capabilities and limitations, and human task allocation. Each chapter represents a case study of the application of HSE from different dimensions of socio-technical systems. The examples are organized using a socio-technical system framework to reference the applications across multiple system types and domains. These case studies serve to illustrate the value of applying HSE to the broader engineering community and provide real world examples. The book provides reference examples in a variety of domains and applications to educate engineers; the integration of the human user is listed as one of the enablers of System Engineering (SE) in the System Engineering Body of Knowledge (SEBoK)."--

Systems engineering. --- Human engineering.

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Mathematics --- Mathematical models. --- Computer simulation. --- Vocational guidance.

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This broad-ranging text/reference presents a fascinating review of the state of the art of modeling and simulation, highlighting both the seminal work of preeminent authorities and exciting developments from promising young researchers in the field. Celebrating the 50th anniversary of the Winter Simulation Conference (WSC), the premier international forum for disseminating recent advances in the field of system simulation, the book showcases the historical importance of this influential conference while also looking forward to a bright future for the simulation community. Topics and features: Examines the challenge of constructing valid and efficient models, emphasizing the benefits of the process of simulation modeling Discusses model calibration, input model risk, and approaches to validating emergent behaviors in large-scale compl ex systems with non-linear interactions Reviews the evolution of simulation languages, and the history of the Time Warp algorithm Offers a focus on the design and analysis of simulation experiments under various goals, and describes how data can be “farmed” to support decision making Provides a comprehensive overview of Bayesian belief models for simulation-based decision making, and introduces a model for ranking and selection in cloud computing Highlights how input model uncertainty impacts simulation optimization, and proposes an approach to quantify and control the impact of input model risk Surveys the applications of simulation in semiconductor manufacturing, in social and behavioral modeling, and in military planning and training Presents data analysis on the publications from the Winter Simulation Conference, offering a big-data perspective on the significant impact of the conference This informative and inspiring volume will appeal to all academics and professionals interested in computational and mathematical modeling and simulation, as well as to graduate students on the path to form the next generation of WSC pioneers. Dr. Andreas Tolk is a Technology Integrator at The MITRE Corporation, Hampton, VA, USA, and adjunct Professor at Old Dominion University, Norfolk, VA, USA. Dr. John Fowler is the Motorola Professor of Supply Chain Management in the W.P. Carey School of Business at Arizona State University, AZ, Tempe, USA. Dr. Guodong Shao is a Computer Scientist in the Systems Integration Division (SID) of the Engineering Laboratory (EL) at the National Institute of Standards and Technology (NIST), Gaithersburg, MD, USA. Dr. Enver Yücesan is a Professor of Operations Management at INSEAD, Fontainebleau, France.

Computer science. --- Computer simulation. --- Computer-aided engineering. --- Mathematical models. --- Operations research. --- Management science. --- Computer Science. --- Simulation and Modeling. --- Mathematical Modeling and Industrial Mathematics. --- Computer-Aided Engineering (CAD, CAE) and Design. --- Operations Research, Management Science. --- Computer modeling --- Computer models --- Modeling, Computer --- Models, Computer --- Simulation, Computer --- Electromechanical analogies --- Mathematical models --- Simulation methods --- Model-integrated computing --- Computer aided design. --- CAD (Computer-aided design) --- Computer-assisted design --- Computer-aided engineering --- Design --- Quantitative business analysis --- Management --- Problem solving --- Operations research --- Statistical decision --- Operational analysis --- Operational research --- Industrial engineering --- Management science --- Research --- System theory --- CAE --- Engineering --- Models, Mathematical --- Data processing