The Logic Programming Paradigm: A 25-Year Perspective (Artificial Intelligence)

ISBN 10: 3642642497 / ISBN 13: 9783642642494

Verlag: Springer, 2011

Beschreibung

Like New. Bestandsnummer des Verkäufers ERICA79636426424976

Bibliografische Details

Titel: The Logic Programming Paradigm: A 25-Year ...

Verlag: Springer

Erscheinungsdatum: 2011

Einband: Paperback

Zustand: Like New

Art des Buches: book

Über diesen Titel

Inhaltsangabe:

Logic Programming was founded 25 years ago. This exciting new text reveals both the evolution of this programming paradigm since its inception and the impressively broad scope of current research in Logic Programming. The contributions to the book deal with both theoretical and practical issues. They address such diverse topics as: computational molecular biology, machine learning, mobile computing, multi-agent systems, planning, numerical computing and dynamical systems, database systems, an alternative to the "formulas as types" approach, program semantics and analysis, and natural language processing. The contributors are all leading world experts in Logic Programming and their contributions were all invited and refereed.

Reseña del editor:

This exciting new text reveals both the evolution of this programming paradigm since its inception and the impressively broad scope of current research in the field. The contributors to this book are all leading world experts in Logic Programming, and they deal with both theoretical and practical issues. They address such diverse topics as: computational molecular biology, machine learning, mobile computing, multi-agent systems, planning, numerical computing and dynamical systems, database systems, an alternative to the "formulas as types" approach, program semantics and analysis, and natural language processing. XXXXXXX Neuer Text Logic Programming was founded 25 years ago. This exciting book reveals both the evolution of this programming paradigm and its impressively broad scope of current research. The contributions by leading computer scientists deal with both theoretical and practical issues. They address diverse topics such as: computational molecular biology, machine learning, mobile computing, multi-agent systems, numerical computing and dynamical systems, database systems, program semantics, natural language processing, and promising future directions.