TY - BOOK ID - 218697 TI - Knowledge-driven computing : knowledge engineering and intelligent computations PY - 2008 SN - 3540774750 3540774742 PB - Berlin ; Heidelberg : Springer, DB - UniCat KW - Engineering. KW - Artificial intelligence. KW - Applied mathematics. KW - Engineering mathematics. KW - Appl.Mathematics/Computational Methods of Engineering. KW - Artificial Intelligence (incl. Robotics). KW - Applications of Mathematics. KW - Engineering KW - Engineering analysis KW - Mathematical analysis KW - AI (Artificial intelligence) KW - Artificial thinking KW - Electronic brains KW - Intellectronics KW - Intelligence, Artificial KW - Intelligent machines KW - Machine intelligence KW - Thinking, Artificial KW - Bionics KW - Cognitive science KW - Digital computer simulation KW - Electronic data processing KW - Logic machines KW - Machine theory KW - Self-organizing systems KW - Simulation methods KW - Fifth generation computers KW - Neural computers KW - Construction KW - Industrial arts KW - Technology KW - Mathematics KW - Knowledge acquisition (Expert systems) KW - Expert systems (Computer science) KW - Acquisition, Knowledge (Expert systems) KW - Expertise acquisition (Expert systems) KW - Knowledge-based systems (Computer science) KW - Systems, Expert (Computer science) KW - Artificial intelligence KW - Computer systems KW - Soft computing KW - Mathematics. KW - Mathematical and Computational Engineering. KW - Artificial Intelligence. KW - Math KW - Science UR - https://www.unicat.be/uniCat?func=search&query=sysid:218697 AB - Knowledge-Driven Computing constitutes an emerging area of intensive research located at the intersection of Computational Intelligence and Knowledge Engineering with strong mathematical foundations. It embraces methods and approaches coming from diverse computational paradigms, such as evolutionary computation and nature-inspired algorithms, logic programming and constraint programming, rule-based systems, fuzzy sets and many others. The use of various knowledge representation formalisms and knowledge processing and computing paradigms is oriented towards the efficient resolution of computationally complex and difficult problems. The main aim of this volume has been to gather together a selection of recent papers providing new ideas and solutions for a wide spectrum of Knowledge-Driven Computing approaches. More precisely, the ultimate goal has been to collect new knowledge representation, processing and computing paradigms which could be useful to practitioners involved in the area of discussion. To this end, contributions covering both theoretical aspects and practical solutions, and dealing with topics of interest for a wide audience, and/or cross-disciplinary research were preferred. ER -