Statistical Relational Artificial Intelligence

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Statistical Relational Artificial Intelligence

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Author : Luc De Raedt
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2016-03-24

Statistical Relational Artificial Intelligence written by Luc De Raedt and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-24 with Computers categories.

An intelligent agent interacting with the real world will encounter individual people, courses, test results, drugs prescriptions, chairs, boxes, etc., and needs to reason about properties of these individuals and relations among them as well as cope with uncertainty. Uncertainty has been studied in probability theory and graphical models, and relations have been studied in logic, in particular in the predicate calculus and its extensions. This book examines the foundations of combining logic and probability into what are called relational probabilistic models. It introduces representations, inference, and learning techniques for probability, logic, and their combinations. The book focuses on two representations in detail: Markov logic networks, a relational extension of undirected graphical models and weighted first-order predicate calculus formula, and Problog, a probabilistic extension of logic programs that can also be viewed as a Turing-complete relational extension of Bayesian networks.

Statistical Relational Artificial Intelligence

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Author : Luc De Raedt
language : en
Publisher: Springer Nature
Release Date : 2022-05-31

Statistical Relational Artificial Intelligence written by Luc De Raedt and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.

An intelligent agent interacting with the real world will encounter individual people, courses, test results, drugs prescriptions, chairs, boxes, etc., and needs to reason about properties of these individuals and relations among them as well as cope with uncertainty. Uncertainty has been studied in probability theory and graphical models, and relations have been studied in logic, in particular in the predicate calculus and its extensions. This book examines the foundations of combining logic and probability into what are called relational probabilistic models. It introduces representations, inference, and learning techniques for probability, logic, and their combinations. The book focuses on two representations in detail: Markov logic networks, a relational extension of undirected graphical models and weighted first-order predicate calculus formula, and Problog, a probabilistic extension of logic programs that can also be viewed as a Turing-complete relational extension of Bayesian networks.

Statistical Relational Artificial Intelligence In Photovoltaic Power Uncertainty Analysis

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Author : Xueqian Fu
language : en
Publisher: Elsevier
Release Date : 2025-04-16

Statistical Relational Artificial Intelligence In Photovoltaic Power Uncertainty Analysis written by Xueqian Fu and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-16 with Science categories.

Statistical Relational Artificial Intelligence in Photovoltaic Power Uncertainty Analysis addresses uncertainty issues in photovoltaic power generation while also supporting the collaborative enhancement of understanding and applying theory and methods through the integration of models, cases, and code. The book employs StaRAI to address uncertainty analysis and modeling issues at different time scales in photovoltaic power generation, including photovoltaic power prediction, probabilistic power flow, stochastic planning, and more. Chapters cover uncertainty of PV power generation from short to long time scales, including day-ahead scheduling (24 hours in advance), intraday scheduling (minute to hour rolling), and grid planning (15 years).Other sections study the impact of photovoltaic uncertainty on the power grid, offering the most classic cases of probabilistic load flow and PV stochastic planning.The theoretical content of this book is not only systematic but supplemented with concrete examples and MATLAB/Python codes. Its contents will be of interest to all those working on photovoltaic planning, power generation, power plants, and applications of AI, including researchers, advanced students, faculty engineers, R&D, and designers. - Explores how Statistical Relational Artificial Intelligence (StaRAI) can be applied to photovoltaic power prediction, maintenance, and planning - Provides a theoretical framework supported by schematic diagrams, real examples, and code - Discusses the potential for groundbreaking AI applications in PV, future opportunities, and ethical and societal impacts

Logical And Relational Learning

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Author : Luc De Raedt
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-09-27

Logical And Relational Learning written by Luc De Raedt and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-09-27 with Computers categories.

This first textbook on multi-relational data mining and inductive logic programming provides a complete overview of the field. It is self-contained and easily accessible for graduate students and practitioners of data mining and machine learning.

Statistical Relational Artificial Intelligence

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Author : Kristian Kersting
language : en
Publisher:
Release Date : 2010-07-11

Statistical Relational Artificial Intelligence written by Kristian Kersting and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07-11 with categories.

Perspectives On Logics For Data Driven Reasoning

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Author : Hykel Hosni
language : en
Publisher: Springer Nature
Release Date : 2025-01-21

Perspectives On Logics For Data Driven Reasoning written by Hykel Hosni and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-21 with Science categories.

This book calls for a rethinking of logic as the core methodological tool for scientific reasoning in the context of a steadily increasing emphasis on data-centered science. To do so it provides a state-of-the-art presentation of the role logic can have in making the most of the current opportunities while making explicit the key challenges opened up by the data-driven age of scientific research. Particular attention is given to the following four core fields and applications: Reasoning with correlations (medical, life-science applications); logics for statistical inference (machine learning, and societal applications thereof); reasoning with evidence (defining good evidence); causal reasoning (forensic reasoning). The book collects contributions from key logicians, methodologists and scientists. This multidisciplinary perspective benefits both scientists and logicians interested in data-driven science. Scientists are introduced to logics that go beyond classical and thus are applicable to reasoning with data; Logicians have a change to focus on the potential applications of their methods and techniques to pressing scientific problems. This book is, therefore, of interest to scientists and logicians working on data-centered science.

Ensemble Methods For Machine Learning

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Author : Gautam Kunapuli
language : en
Publisher: Simon and Schuster
Release Date : 2023-05-02

Ensemble Methods For Machine Learning written by Gautam Kunapuli and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-02 with Computers categories.

Many machine learning problems are too complex to be resolved by a single model or algorithm. Ensemble machine learning trains a group of diverse machine learning models to work together to solve a problem. By aggregating their output, these ensemble models can flexibly deliver rich and accurate results. Ensemble Methods for Machine Learning is a guide to ensemble methods with proven records in data science competitions and real-world applications. Learning from hands-on case studies, you'll develop an under-the-hood understanding of foundational ensemble learning algorithms to deliver accurate, performant models.

Artificial Intelligence Machine Learning In Marketing

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Author : James Seligman
language : en
Publisher: Lulu.com
Release Date : 2020-02-17

Artificial Intelligence Machine Learning In Marketing written by James Seligman and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-17 with Business & Economics categories.

The theory and practice of AI and ML in marketing saving time, money

Ki 2016 Advances In Artificial Intelligence

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Author : Gerhard Friedrich
language : en
Publisher: Springer
Release Date : 2016-09-08

Ki 2016 Advances In Artificial Intelligence written by Gerhard Friedrich and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-08 with Computers categories.

This book constitutes the refereed proceedings of the 39th Annual German Conference on Artificial Intelligence, KI 2016, in conjunction with the Österreichische Gesellschaft für Artificial Intelligence, ÖGAI, held in Klagenfurt, Austria, in September 2016. The 8 revised full technical papers presented together with 12 technical communications, and 16 extended abstracts were carefully reviewed and selected from 44 submissions. The conference provides the opportunity to present a wider range of results and ideas that are of interest to the KI audience, including reports about recent own publications, position papers, and previews of ongoing work.

Logics In Artificial Intelligence

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Author : Sarah Gaggl
language : en
Publisher: Springer Nature
Release Date : 2023-09-23

Logics In Artificial Intelligence written by Sarah Gaggl and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-23 with Computers categories.

This book constitutes proceedings of the 18th European Conference on Logics in Artificial Intelligence, JELIA 2023, held in Dresden, Germany, in September 2023. The 41 full papers and 11 short papers included in this volume were carefully reviewed and selected from 111 submissions. The accepted papers span a number of areas within Logics in AI, including: argumentation; belief revision; reasoning about actions, causality, and change; constraint satisfaction; description logics and ontological reasoning; non-classical logics; and logic programming (answer set programming).