Algorithmic Intelligence

Towards an Algorithmic Foundation for Artificial Intelligence

Inbunden, Engelska, 2023

2 929 kr

Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt för medlemmar vid köp för minst 249 kr.

In 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.

Produktinformation

Utgivningsdatum2023-05-31
Mått210 x 279 x 35 mm
Vikt1 428 g
FormatInbunden
SpråkEngelska
Antal sidor467
FörlagSpringer International Publishing AG
ISBN9783319655956

Tillhör följande kategorier

Systemvetenskap och AI inom Data och it
Elektronik och kommunikationer inom Naturvetenskap och teknik
Artificiell intelligens inom Data och it
Projektledning inom Ekonomi och ledarskap
Affärsapplikationer inom Data och it
Databaser inom Data och it
Affärsförhandlingar inom Ekonomi och ledarskap

Prof. Dr. Stefan Edelkamp is full professor at the Czech Technical University in Prague. Previously he was the leader of the planning group at King's College London, and also worked at the Institute for Artificial Intelligence, Faculty of Computer Science and Mathematics of the University of Bremen, and at the University of Applied Science in Darmstadt. For a short period of time, he held the position of an Interim Professor at the University of Koblenz and Landau and Paris Dauphine University. He earned his Ph.D. from Freiburg University and led a junior research group at the Technical University of Dortmund. His main scientific interest is algorithmic intelligence, which encompasses areas such as heuristic search, action planning, game playing, machine learning, motion planning, multiagent simulation, model checking, distributed computing, algorithm engineering, and computational biology.

Preface.- 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