Name: Causal Discovery: Foundations, Algorithms and Applications (Computer Science Foundations and Applied Logic) (en Inglés)
Price: 87.93 USD
Availability: InStock
Author: Luis Enrique Sucar
ISBN: 9783031983443

portada Causal Discovery: Foundations, Algorithms and Applications (Computer Science Foundations and Applied Logic) (en Inglés)

Causal Discovery: Foundations, Algorithms and Applications (Computer Science Foundations and Applied Logic) (en Inglés)

Formato

Libro Físico

Editorial

Birkhauser

Autor

Luis Enrique Sucar

Idioma

Inglés

N° páginas

250

Encuadernación

Tapa Dura

ISBN13

9783031983443

Causal Discovery: Foundations, Algorithms and Applications (Computer Science Foundations and Applied Logic) (en Inglés)

Luis Enrique Sucar (Autor) · Birkhauser · Tapa Dura

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Reseña del libro "Causal Discovery: Foundations, Algorithms and Applications (Computer Science Foundations and Applied Logic) (en Inglés)"

This book presents an overview of causal discovery, an emergent field with important developments in the last few years, and multiple applications in several fields. The book is divided into three parts. The first part provides the necessary background on causal graphical models and causal reasoning. The second describes the main algorithms and techniques for causal discovery: (a) causal discovery from observational data, (b) causal discovery from interventional data, (c) causal discovery from temporal data, and (d) causal reinforcement learning. The third part provides several examples of causal discovery in practice, including applications in biomedicine, social sciences, artificial intelligence and robotics. Topics and features: Covers the main types of causal discovery: learning from observational data, learning from interventional data, and learning from temporal data This book can be used as a textbook for an advanced undergraduate or a graduate course on causal discovery for students of computer science, engineering, social sciences, etc. It can also be used as a complement to a course on causality, together with another text on causal reasoning. It could also serve as a reference book for professionals that want to apply causal models in different areas, or anyone who is interested in knowing the basis of these techniques. The intended audience are students and professionals in computer science, statistics and engineering who want to know the principles of causal discovery and / or applied them in different domains. It could also be of interest to students and professionals in other areas who want to apply causal discovery, for instance in medicine and economics.