LEADER 04611nam 22007335 450 001 9910728939503321 005 20230530164122.0 010 $a9783319655963$b(electronic bk.) 010 $z9783319655956 024 7 $a10.1007/978-3-319-65596-3 035 $a(MiAaPQ)EBC30555907 035 $a(Au-PeEL)EBL30555907 035 $a(OCoLC)1381095126 035 $a(DE-He213)978-3-319-65596-3 035 $a(BIP)060217650 035 $a(PPN)270616411 035 $a(CKB)26806715400041 035 $a(EXLCZ)9926806715400041 100 $a20230530d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAlgorithmic Intelligence $eTowards an Algorithmic Foundation for Artificial Intelligence /$fby Stefan Edelkamp 205 $a1st ed. 2023. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2023. 215 $a1 online resource (482 pages) 311 08$aPrint version: Edelkamp, Stefan Algorithmic Intelligence Cham : Springer International Publishing AG,c2023 9783319655956 327 $aPreface -- Towards a Characterization -- Part I, Basics -- 1. Programming Primer -- 2. Shortest Paths -- 3. Sorting -- 4. Deep Learning -- 5. Monte-Carlo Search -- Part II, Big Data -- 6. Graph data -- 7. Multimedia Data -- 8. Network Data -- 9. Image Data -- 10. Navigation Data -- Part III, Research Areas -- 11. Machine Learning -- 12. Problem Solving -- 13. Card Game Playing -- 14. Action Planning -- 15. General Game Playing -- 16. Multiagent Systems -- 17. Recommendation and Configuration Part IV, Applications -- 18. Adversarial Planning -- 19. Model Checking -- 20. Computational Biology -- 21. Logistics -- 22. Additive Manufacturing -- 23. Robot Motion Planning -- 24. Industrial Production -- 25. Further Application Areas. - Index and References. 330 $aIn this book the author argues that the basis of what we consider computer intelligence has algorithmic roots, and he presents this with a holistic view, showing examples and explaining approaches that encompass theoretical computer science and machine learning via engineered algorithmic solutions. Part I of the book introduces the basics. The author starts with a hands-on programming primer for solving combinatorial problems, with an emphasis on recursive solutions. The other chapters in the first part of the book explain shortest paths, sorting, deep learning, and Monte Carlo search. A key function of computational tools is processing Big Data efficiently, and the chapters in Part II of the book examine traditional graph problems such as finding cliques, colorings, independent sets, vertex covers, and hitting sets, and the subsequent chapters cover multimedia, network, image, and navigation data. The highly topical research areas detailed in Part III are machine learning, problem solving, action planning, general game playing, multiagent systems, and recommendation and configuration. Finally, in Part IV the author uses application areas such as model checking, computational biology, logistics, additive manufacturing, robot motion planning, and industrial production to explain how the techniques described may be exploited in modern settings. The book is supported with a comprehensive index and references, and it will be of value to researchers, practitioners, and students in the areas of artificial intelligence and computational intelligence. 606 $aArtificial intelligence 606 $aData mining 606 $aControl engineering 606 $aRobotics 606 $aAutomation 606 $aBusiness information services 606 $aBusiness logistics 606 $aArtificial Intelligence 606 $aData Mining and Knowledge Discovery 606 $aControl, Robotics, Automation 606 $aIT in Business 606 $aLogistics 610 $aScience 615 0$aArtificial intelligence. 615 0$aData mining. 615 0$aControl engineering. 615 0$aRobotics. 615 0$aAutomation. 615 0$aBusiness information services. 615 0$aBusiness logistics. 615 14$aArtificial Intelligence. 615 24$aData Mining and Knowledge Discovery. 615 24$aControl, Robotics, Automation. 615 24$aIT in Business. 615 24$aLogistics. 676 $a006.3 700 $aEdelkamp$b Stefan$0853901 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910728939503321 996 $aAlgorithmic Intelligence$93389825 997 $aUNINA