Inductive Logic Programming [electronic resource] : 31st International Conference, ILP 2022, Windsor Great Park, UK, September 28-30, 2022, Proceedings / edited by Stephen H. Muggleton, Alireza Tamaddoni-Nezhad.
Contributor(s): Muggleton, Stephen H [editor.]
| Tamaddoni-Nezhad, Alireza [editor.] | SpringerLink (Online service).
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BookSeries: Lecture Notes in Artificial Intelligence: 13779Publisher: Cham : Springer Nature Switzerland : Imprint: Springer, 2024Edition: 1st ed. 2024.Description: X, 157 p. 35 illus., 20 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783031556302.Subject(s): Artificial intelligence | Computer engineering | Computer networks | Compilers (Computer programs) | Computer science | Machine theory | Artificial Intelligence | Computer Engineering and Networks | Compilers and Interpreters | Computer Science Logic and Foundations of Programming | Formal Languages and Automata TheoryAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
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Springer Nature eBookSummary: This book constitutes the refereed proceedings of the 31st International Conference on Inductive Logic Programming, ILP 2022, held during September 28-30, 2022. The 11 regular papers presented in this book were carefully reviewed and selected from 26 submissions The papers in these proceedings represent the diversity and vitality in present ILP research, including statistical relational learning, transfer learning, scientific reasoning, learning temporal models, synthesis and planning, and argumentation and language. .
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This book constitutes the refereed proceedings of the 31st International Conference on Inductive Logic Programming, ILP 2022, held during September 28-30, 2022. The 11 regular papers presented in this book were carefully reviewed and selected from 26 submissions The papers in these proceedings represent the diversity and vitality in present ILP research, including statistical relational learning, transfer learning, scientific reasoning, learning temporal models, synthesis and planning, and argumentation and language. .
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