Explainable Fuzzy Systems

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Explainable Fuzzy Systems

Jose Maria Alonso Moral,Ciro Castiello,Luis Magdalena,Corrado Mencar
Explainable Fuzzy Systems Book PDF

Author : Jose Maria Alonso Moral,Ciro Castiello,Luis Magdalena,Corrado Mencar
Publisher : Springer Nature
Page : 232 pages
File Size : 41,8 Mb
Release : 2021-04-07
Category : Technology & Engineering
ISBN : 9783030710989

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Explainable Fuzzy Systems by Jose Maria Alonso Moral,Ciro Castiello,Luis Magdalena,Corrado Mencar Pdf

The importance of Trustworthy and Explainable Artificial Intelligence (XAI) is recognized in academia, industry and society. This book introduces tools for dealing with imprecision and uncertainty in XAI applications where explanations are demanded, mainly in natural language. Design of Explainable Fuzzy Systems (EXFS) is rooted in Interpretable Fuzzy Systems, which are thoroughly covered in the book. The idea of interpretability in fuzzy systems, which is grounded on mathematical constraints and assessment functions, is firstly introduced. Then, design methodologies are described. Finally, the book shows with practical examples how to design EXFS from interpretable fuzzy systems and natural language generation. This approach is supported by open source software. The book is intended for researchers, students and practitioners who wish to explore EXFS from theoretical and practical viewpoints. The breadth of coverage will inspire novel applications and scientific advancements.

Explainable Artificial Intelligence Based on Neuro-Fuzzy Modeling with Applications in Finance

Tom Rutkowski
Explainable Artificial Intelligence Based on Neuro Fuzzy Modeling with Applications in Finance Book PDF

Author : Tom Rutkowski
Publisher : Springer Nature
Page : 167 pages
File Size : 47,5 Mb
Release : 2021-06-07
Category : Technology & Engineering
ISBN : 9783030755218

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Explainable Artificial Intelligence Based on Neuro-Fuzzy Modeling with Applications in Finance by Tom Rutkowski Pdf

The book proposes techniques, with an emphasis on the financial sector, which will make recommendation systems both accurate and explainable. The vast majority of AI models work like black box models. However, in many applications, e.g., medical diagnosis or venture capital investment recommendations, it is essential to explain the rationale behind AI systems decisions or recommendations. Therefore, the development of artificial intelligence cannot ignore the need for interpretable, transparent, and explainable models. First, the main idea of the explainable recommenders is outlined within the background of neuro-fuzzy systems. In turn, various novel recommenders are proposed, each characterized by achieving high accuracy with a reasonable number of interpretable fuzzy rules. The main part of the book is devoted to a very challenging problem of stock market recommendations. An original concept of the explainable recommender, based on patterns from previous transactions, is developed; it recommends stocks that fit the strategy of investors, and its recommendations are explainable for investment advisers.

Explainable AI and Other Applications of Fuzzy Techniques

Julia Rayz,Victor Raskin,Scott Dick,Vladik Kreinovich
Explainable AI and Other Applications of Fuzzy Techniques Book PDF

Author : Julia Rayz,Victor Raskin,Scott Dick,Vladik Kreinovich
Publisher : Springer Nature
Page : 506 pages
File Size : 48,8 Mb
Release : 2021-07-27
Category : Technology & Engineering
ISBN : 9783030820992

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Explainable AI and Other Applications of Fuzzy Techniques by Julia Rayz,Victor Raskin,Scott Dick,Vladik Kreinovich Pdf

This book focuses on an overview of the AI techniques, their foundations, their applications, and remaining challenges and open problems. Many artificial intelligence (AI) techniques do not explain their recommendations. Providing natural-language explanations for numerical AI recommendations is one of the main challenges of modern AI. To provide such explanations, a natural idea is to use techniques specifically designed to relate numerical recommendations and natural-language descriptions, namely fuzzy techniques. This book is of interest to practitioners who want to use fuzzy techniques to make AI applications explainable, to researchers who may want to extend the ideas from these papers to new application areas, and to graduate students who are interested in the state-of-the-art of fuzzy techniques and of explainable AI—in short, to anyone who is interested in problems involving fuzziness and AI in general.

Towards Explainable Fuzzy AI: Concepts, Paradigms, Tools, and Techniques

Vladik Kreinovich
Towards Explainable Fuzzy AI Concepts Paradigms Tools and Techniques Book PDF

Author : Vladik Kreinovich
Publisher : Springer Nature
Page : 136 pages
File Size : 41,8 Mb
Release : 2022-09-16
Category : Technology & Engineering
ISBN : 9783031099748

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Towards Explainable Fuzzy AI: Concepts, Paradigms, Tools, and Techniques by Vladik Kreinovich Pdf

Modern AI techniques –- especially deep learning –- provide, in many cases, very good recommendations: where a self-driving car should go, whether to give a company a loan, etc. The problem is that not all these recommendations are good -- and since deep learning provides no explanations, we cannot tell which recommendations are good. It is therefore desirable to provide natural-language explanation of the numerical AI recommendations. The need to connect natural language rules and numerical decisions is known since 1960s, when the need emerged to incorporate expert knowledge -- described by imprecise words like "small" -- into control and decision making. For this incorporation, a special "fuzzy" technique was invented, that led to many successful applications. This book described how this technique can help to make AI more explainable.The book can be recommended for students, researchers, and practitioners interested in explainable AI.

Explainable Uncertain Rule-Based Fuzzy Systems

Jerry M. Mendel
Explainable Uncertain Rule Based Fuzzy Systems Book PDF

Author : Jerry M. Mendel
Publisher : Springer
Page : 0 pages
File Size : 49,8 Mb
Release : 2023-09-12
Category : Technology & Engineering
ISBN : 3031353773

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Explainable Uncertain Rule-Based Fuzzy Systems by Jerry M. Mendel Pdf

The third edition of this textbook presents a further updated approach to fuzzy sets and systems that can model uncertainty — i.e., “type-2” fuzzy sets and systems. The author demonstrates how to overcome the limitations of classical fuzzy sets and systems, enabling a wide range of applications, from time-series forecasting to knowledge mining to classification to control and to explainable AI (XAI). This latest edition again begins by introducing classical (type-1) fuzzy sets and systems, and then explains how they can be modified to handle uncertainty, leading to type-2 fuzzy sets and systems. New material is included about how to obtain fuzzy set word models that are needed for XAI, similarity of fuzzy sets, a quantitative methodology that lets one explain in a simple way why the different kinds of fuzzy systems have the potential for performance improvements over each other, and new parameterizations of membership functions that have the potential for achieving even greater performance for all kinds of fuzzy systems. For hands-on experience, the book provides information on accessing MATLAB, Java, and Python software to complement the content. The book features a full suite of classroom material.

Uncertain Rule-Based Fuzzy Systems

Jerry M. Mendel
Uncertain Rule Based Fuzzy Systems Book PDF

Author : Jerry M. Mendel
Publisher : Springer
Page : 684 pages
File Size : 52,7 Mb
Release : 2017-05-17
Category : Technology & Engineering
ISBN : 9783319513706

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Uncertain Rule-Based Fuzzy Systems by Jerry M. Mendel Pdf

The second edition of this textbook provides a fully updated approach to fuzzy sets and systems that can model uncertainty — i.e., “type-2” fuzzy sets and systems. The author demonstrates how to overcome the limitations of classical fuzzy sets and systems, enabling a wide range of applications from time-series forecasting to knowledge mining to control. In this new edition, a bottom-up approach is presented that begins by introducing classical (type-1) fuzzy sets and systems, and then explains how they can be modified to handle uncertainty. The author covers fuzzy rule-based systems – from type-1 to interval type-2 to general type-2 – in one volume. For hands-on experience, the book provides information on accessing MatLab and Java software to complement the content. The book features a full suite of classroom material.

Explainable AI: Interpreting, Explaining and Visualizing Deep Learning

Wojciech Samek,Grégoire Montavon,Andrea Vedaldi,Lars Kai Hansen,Klaus-Robert Müller
Explainable AI Interpreting Explaining and Visualizing Deep Learning Book PDF

Author : Wojciech Samek,Grégoire Montavon,Andrea Vedaldi,Lars Kai Hansen,Klaus-Robert Müller
Publisher : Springer Nature
Page : 435 pages
File Size : 42,6 Mb
Release : 2019-09-10
Category : Computers
ISBN : 9783030289546

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Explainable AI: Interpreting, Explaining and Visualizing Deep Learning by Wojciech Samek,Grégoire Montavon,Andrea Vedaldi,Lars Kai Hansen,Klaus-Robert Müller Pdf

The development of “intelligent” systems that can take decisions and perform autonomously might lead to faster and more consistent decisions. A limiting factor for a broader adoption of AI technology is the inherent risks that come with giving up human control and oversight to “intelligent” machines. For sensitive tasks involving critical infrastructures and affecting human well-being or health, it is crucial to limit the possibility of improper, non-robust and unsafe decisions and actions. Before deploying an AI system, we see a strong need to validate its behavior, and thus establish guarantees that it will continue to perform as expected when deployed in a real-world environment. In pursuit of that objective, ways for humans to verify the agreement between the AI decision structure and their own ground-truth knowledge have been explored. Explainable AI (XAI) has developed as a subfield of AI, focused on exposing complex AI models to humans in a systematic and interpretable manner. The 22 chapters included in this book provide a timely snapshot of algorithms, theory, and applications of interpretable and explainable AI and AI techniques that have been proposed recently reflecting the current discourse in this field and providing directions of future development. The book is organized in six parts: towards AI transparency; methods for interpreting AI systems; explaining the decisions of AI systems; evaluating interpretability and explanations; applications of explainable AI; and software for explainable AI.

Theory and Practice of Natural Computing

David Fagan,Carlos Martín-Vide,Michael O'Neill,Miguel A. Vega-Rodríguez
Theory and Practice of Natural Computing Book PDF

Author : David Fagan,Carlos Martín-Vide,Michael O'Neill,Miguel A. Vega-Rodríguez
Publisher : Springer
Page : 478 pages
File Size : 43,5 Mb
Release : 2018-12-05
Category : Computers
ISBN : 9783030040703

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Theory and Practice of Natural Computing by David Fagan,Carlos Martín-Vide,Michael O'Neill,Miguel A. Vega-Rodríguez Pdf

This book constitutes the refereed proceedings of the 7th International Conference on Theory and Practice of Natural Computing, TPNC 2017, held in Dublin, Ireland, in December 2018. The 35 full papers presented in this book, together with one invited talk, were carefully reviewed and selected from 69 submissions. The papers are organized around the following topical sections: applications of natural computing as algorithms, bioinformatics, control, cryptography, design, economics. The more theoretical contributions handle with artificial chemistry, artificial immune systems, artificial life, cellular automata, cognitive computing, cognitive engineering, cognitive robotics, collective behaviour, complex systems, computational intelligence, computational social science, computing with words, developmental systems, DNA computing, DNA nanotechnology, evolutionary algorithms, evolutionary computing, evolutionary game theory, fractal geometry, fuzzy control, fuzzy logic, fuzzy sets, fuzzy systems, genetic algorithms, genetic programming, granular computing, heuristics, intelligent agents, intelligent systems, machine intelligence, molecular programming, neural computing, neural networks, quantum communication, quantum computing, rough sets, self-assembly.

Introduction to Fuzzy Sets, Fuzzy Logic, and Fuzzy Control Systems

Guanrong Chen,Trung Tat Pham
Introduction to Fuzzy Sets Fuzzy Logic and Fuzzy Control Systems Book PDF

Author : Guanrong Chen,Trung Tat Pham
Publisher : CRC Press
Page : 328 pages
File Size : 43,5 Mb
Release : 2000-11-27
Category : Mathematics
ISBN : 9781420039818

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Introduction to Fuzzy Sets, Fuzzy Logic, and Fuzzy Control Systems by Guanrong Chen,Trung Tat Pham Pdf

In the early 1970s, fuzzy systems and fuzzy control theories added a new dimension to control systems engineering. From its beginnings as mostly heuristic and somewhat ad hoc, more recent and rigorous approaches to fuzzy control theory have helped make it an integral part of modern control theory and produced many exciting results. Yesterday's "art

Interpretable Artificial Intelligence: A Perspective of Granular Computing

Witold Pedrycz,Shyi-Ming Chen
Interpretable Artificial Intelligence A Perspective of Granular Computing Book PDF

Author : Witold Pedrycz,Shyi-Ming Chen
Publisher : Springer Nature
Page : 430 pages
File Size : 44,7 Mb
Release : 2021-03-26
Category : Technology & Engineering
ISBN : 9783030649494

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Interpretable Artificial Intelligence: A Perspective of Granular Computing by Witold Pedrycz,Shyi-Ming Chen Pdf

This book offers a comprehensive treatise on the recent pursuits of Artificial Intelligence (AI) – Explainable Artificial Intelligence (XAI) by casting the crucial features of interpretability and explainability in the original framework of Granular Computing. The innovative perspective established with the aid of information granules provides a high level of human centricity and transparency central to the development of AI constructs. The chapters reflect the breadth of the area and cover recent developments in the methodology, advanced algorithms and applications of XAI to visual analytics, knowledge representation, learning and interpretation. The book appeals to a broad audience including researchers and practitioners interested in gaining exposure to the rapidly growing body of knowledge in AI and intelligent systems.

Fuzzy Modelling

Witold Pedrycz
Fuzzy Modelling Book PDF

Author : Witold Pedrycz
Publisher : Springer Science & Business Media
Page : 399 pages
File Size : 50,8 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9781461313656

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Fuzzy Modelling by Witold Pedrycz Pdf

Fuzzy Modelling: Paradigms and Practice provides an up-to-date and authoritative compendium of fuzzy models, identification algorithms and applications. Chapters in this book have been written by the leading scholars and researchers in their respective subject areas. Several of these chapters include both theoretical material and applications. The editor of this volume has organized and edited the chapters into a coherent and uniform framework. The objective of this book is to provide researchers and practitioners involved in the development of models for complex systems with an understanding of fuzzy modelling, and an appreciation of what makes these models unique. The chapters are organized into three major parts covering relational models, fuzzy neural networks and rule-based models. The material on relational models includes theory along with a large number of implemented case studies, including some on speech recognition, prediction, and ecological systems. The part on fuzzy neural networks covers some fundamentals, such as neurocomputing, fuzzy neurocomputing, etc., identifies the nature of the relationship that exists between fuzzy systems and neural networks, and includes extensive coverage of their architectures. The last part addresses the main design principles governing the development of rule-based models. Fuzzy Modelling: Paradigms and Practice provides a wealth of specific fuzzy modelling paradigms, algorithms and tools used in systems modelling. Also included is a panoply of case studies from various computer, engineering and science disciplines. This should be a primary reference work for researchers and practitioners developing models of complex systems.

Uncertain Rule-based Fuzzy Logic Systems

Jerry M. Mendel
Uncertain Rule based Fuzzy Logic Systems Book PDF

Author : Jerry M. Mendel
Publisher : Prentice Hall
Page : 584 pages
File Size : 40,9 Mb
Release : 2001
Category : Computers
ISBN : UOM:39015049647897

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Uncertain Rule-based Fuzzy Logic Systems by Jerry M. Mendel Pdf

Jerry Mendel explains the complete development of fuzzy logic systems and explores a new methodology to build better and more intelligent systems. Two case studies are carried throughout the book to illustrate and expand on the theories introduced.

Fuzzy Information Processing 2020

Barnabás Bede,Martine Ceberio,Martine De Cock,Vladik Kreinovich
Fuzzy Information Processing 2020 Book PDF

Author : Barnabás Bede,Martine Ceberio,Martine De Cock,Vladik Kreinovich
Publisher : Springer Nature
Page : 451 pages
File Size : 45,6 Mb
Release : 2021-12-08
Category : Technology & Engineering
ISBN : 9783030815615

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Fuzzy Information Processing 2020 by Barnabás Bede,Martine Ceberio,Martine De Cock,Vladik Kreinovich Pdf

This book describes how to use expert knowledge—which is often formulated by using imprecise (fuzzy) words from a natural language. In the 1960s, Zadeh designed special "fuzzy" techniques for such use. In the 1980s, fuzzy techniques started controlling trains, elevators, video cameras, rice cookers, car transmissions, etc. Now, combining fuzzy with neural, genetic, and other intelligent methods leads to new state-of-the-art results: in aerospace industry (from drones to space flights), in mobile robotics, in finances (predicting the value of crypto-currencies), and even in law enforcement (detecting counterfeit banknotes, detecting online child predators and in creating explainable AI systems). The book describes these (and other) applications—as well as foundations and logistics of fuzzy techniques. This book can be recommended to specialists—both in fuzzy and in various application areas—who will learn latest techniques and their applications, and to students interested in innovative ideas.

Explainable and Interpretable Models in Computer Vision and Machine Learning

Hugo Jair Escalante,Sergio Escalera,Isabelle Guyon,Xavier Baró,Yağmur Güçlütürk,Umut Güçlü,Marcel van Gerven
Explainable and Interpretable Models in Computer Vision and Machine Learning Book PDF

Author : Hugo Jair Escalante,Sergio Escalera,Isabelle Guyon,Xavier Baró,Yağmur Güçlütürk,Umut Güçlü,Marcel van Gerven
Publisher : Springer
Page : 299 pages
File Size : 45,8 Mb
Release : 2018-11-29
Category : Computers
ISBN : 9783319981314

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Explainable and Interpretable Models in Computer Vision and Machine Learning by Hugo Jair Escalante,Sergio Escalera,Isabelle Guyon,Xavier Baró,Yağmur Güçlütürk,Umut Güçlü,Marcel van Gerven Pdf

This book compiles leading research on the development of explainable and interpretable machine learning methods in the context of computer vision and machine learning. Research progress in computer vision and pattern recognition has led to a variety of modeling techniques with almost human-like performance. Although these models have obtained astounding results, they are limited in their explainability and interpretability: what is the rationale behind the decision made? what in the model structure explains its functioning? Hence, while good performance is a critical required characteristic for learning machines, explainability and interpretability capabilities are needed to take learning machines to the next step to include them in decision support systems involving human supervision. This book, written by leading international researchers, addresses key topics of explainability and interpretability, including the following: · Evaluation and Generalization in Interpretable Machine Learning · Explanation Methods in Deep Learning · Learning Functional Causal Models with Generative Neural Networks · Learning Interpreatable Rules for Multi-Label Classification · Structuring Neural Networks for More Explainable Predictions · Generating Post Hoc Rationales of Deep Visual Classification Decisions · Ensembling Visual Explanations · Explainable Deep Driving by Visualizing Causal Attention · Interdisciplinary Perspective on Algorithmic Job Candidate Search · Multimodal Personality Trait Analysis for Explainable Modeling of Job Interview Decisions · Inherent Explainability Pattern Theory-based Video Event Interpretations

Explainable Neural Networks Based on Fuzzy Logic and Multi-criteria Decision Tools

József Dombi,Orsolya Csiszár
Explainable Neural Networks Based on Fuzzy Logic and Multi criteria Decision Tools Book PDF

Author : József Dombi,Orsolya Csiszár
Publisher : Springer Nature
Page : 186 pages
File Size : 41,6 Mb
Release : 2021-04-28
Category : Technology & Engineering
ISBN : 9783030722807

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Explainable Neural Networks Based on Fuzzy Logic and Multi-criteria Decision Tools by József Dombi,Orsolya Csiszár Pdf

The research presented in this book shows how combining deep neural networks with a special class of fuzzy logical rules and multi-criteria decision tools can make deep neural networks more interpretable – and even, in many cases, more efficient. Fuzzy logic together with multi-criteria decision-making tools provides very powerful tools for modeling human thinking. Based on their common theoretical basis, we propose a consistent framework for modeling human thinking by using the tools of all three fields: fuzzy logic, multi-criteria decision-making, and deep learning to help reduce the black-box nature of neural models; a challenge that is of vital importance to the whole research community.