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Foundations of Probabilistic Logic Programming: Languages, Semantics, Inference and Learning book cover

2nd Edition

Foundations of Probabilistic Logic Programming Languages, Semantics, Inference and Learning

By Fabrizio Riguzzi Copyright 2023
548 Pages 22 Color & 75 B/W Illustrations
by River Publishers

548 Pages 22 Color & 75 B/W Illustrations
by River Publishers
Also available as eBook on:
Since its birth, the field of Probabilistic Logic Programming has seen a steady increase of activity, with many proposals for languages and algorithms for inference and learning. This book aims at providing an overview of the field with a special emphasis on languages under the Distribution Semantics, one of the most influential approaches. The book presents the main ideas for semantics,... Read more

1. Preliminaries

2. Probabilistic Logic Programming Languages

3. Semantics with Function Symbols

4. Hybrid Programs

5. Semantics for Hybrid Programs with Function Symbols

6. Probabilistic Answer Set Programming

7. Complexity of Inference

8. Exact Inference

9. Lifted Inference

10. Approximate Inference

11. Non-Standard Inference

12. Inference for Hybrid Programs

13. Parameter Learning

14. Structure Learning

15. cplint Examples

16. Conclusions

Biography

Fabrizio Riguzzi is Full Professor of Computer Science at the Department of Mathematics and Computer Science of the University of Ferrara. He was previously Associate Professor and Assistant Professor at the same university. He obtained his Masters and PhD in Computer Engineering from the University of Bologna. Fabrizio Riguzzi is Editor in Chief of Intelligenza Artificiale, the official journal of the Italian Association for Artificial Intelligence. He is the author of more than 200 peer reviewed papers in the areas of machine learning, inductive logic programming and statistical relational learning. His aim is to develop intelligent systems by combining in novel ways techniques from artificial intelligence, logic and statistics.

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