Uncertainty In Computational Intelligence Based Decision Making

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Uncertainty in Computational Intelligence-Based Decision Making

Author : Ali Ahmadian
Publisher : Elsevier
ISBN 13 : 044321476X
Total Pages : 340 pages
Book Rating : 4.4/5 (432 download)

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Book Synopsis Uncertainty in Computational Intelligence-Based Decision Making by : Ali Ahmadian

Download or read book Uncertainty in Computational Intelligence-Based Decision Making written by Ali Ahmadian and published by Elsevier. This book was released on 2024-09-16 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty in Computational Intelligence-Based Decision-Making focuses on techniques for reasoning and decision-making under uncertainty that are used to solve issues in artificial intelligence (AI). It covers a wide range of subjects, including knowledge acquisition and automated model construction, pattern recognition, machine learning, natural language processing, decision analysis, and decision support systems, among others. The first chapter of this book provides a thorough introduction to the topics of causation in Bayesian belief networks, applications of uncertainty, automated model construction and learning, graphic models for inference and decision making, and qualitative reasoning. The following chapters examine the fundamental models of computational techniques, computational modeling of biological and natural intelligent systems, including swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems, and evolutionary computation. They also examine decision making and analysis, expert systems, and robotics in the context of artificial intelligence and computer science. Provides readers a thorough understanding of the uncertainty that arises in artificial intelligence (AI), computational intelligence (CI) paradigms, and algorithms Encourages readers to put concepts into practice and solve complex real-world problems using CI development frameworks like decision support systems and visual decision design Provides a comprehensive overview of the techniques used in computational intelligence, uncertainty, and decision

Decision Making Under Uncertainty

Author : Mykel J. Kochenderfer
Publisher : MIT Press
ISBN 13 : 0262331713
Total Pages : 350 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Decision Making Under Uncertainty by : Mykel J. Kochenderfer

Download or read book Decision Making Under Uncertainty written by Mykel J. Kochenderfer and published by MIT Press. This book was released on 2015-07-24 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to decision making under uncertainty from a computational perspective, covering both theory and applications ranging from speech recognition to airborne collision avoidance. Many important problems involve decision making under uncertainty—that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines.

Intelligent Decision Making: An AI-Based Approach

Author : Gloria Phillips-Wren
Publisher : Springer Science & Business Media
ISBN 13 : 3540768289
Total Pages : 414 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Intelligent Decision Making: An AI-Based Approach by : Gloria Phillips-Wren

Download or read book Intelligent Decision Making: An AI-Based Approach written by Gloria Phillips-Wren and published by Springer Science & Business Media. This book was released on 2008-03-04 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent Decision Support Systems have the potential to transform human decision making by combining research in artificial intelligence, information technology, and systems engineering. The field of intelligent decision making is expanding rapidly due, in part, to advances in artificial intelligence and network-centric environments that can deliver the technology. Communication and coordination between dispersed systems can deliver just-in-time information, real-time processing, collaborative environments, and globally up-to-date information to a human decision maker. At the same time, artificial intelligence techniques have demonstrated that they have matured sufficiently to provide computational assistance to humans in practical applications. This book includes contributions from leading researchers in the field beginning with the foundations of human decision making and the complexity of the human cognitive system. Researchers contrast human and artificial intelligence, survey computational intelligence, present pragmatic systems, and discuss future trends. This book will be an invaluable resource to anyone interested in the current state of knowledge and key research gaps in the rapidly developing field of intelligent decision support.

Uncertainty Modeling in Knowledge Engineering and Decision Making

Author :
Publisher : World Scientific
ISBN 13 : 9814417742
Total Pages : 1373 pages
Book Rating : 4.8/5 (144 download)

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Book Synopsis Uncertainty Modeling in Knowledge Engineering and Decision Making by :

Download or read book Uncertainty Modeling in Knowledge Engineering and Decision Making written by and published by World Scientific. This book was released on 2012 with total page 1373 pages. Available in PDF, EPUB and Kindle. Book excerpt: FLINS, originally an acronym for Fuzzy Logic and Intelligent Technologies in Nuclear Science, is now extended to Computational Intelligence for applied research. The contributions to the 10th of FLINS conference cover state-of-the-art research, development, and technology for computational intelligence systems, both from the foundations and the applications points-of-view. Sample Chapter(s). Foreword (55 KB). Evaluation of Manufacturing Technology of Photovoltaic Cells (124 KB). Contents: Decision Making and Decision Support Systems; Uncertainty Modeling; Foundations of Computational Intelligence; Statistics, Data Analysis and Data Mining; Intelligent Information Processing; Productivity and Reliability; Applied Research. Readership: Graduate students, researchers, and academics in artificial intelligence/machine learning, information management, decision sciences, databases/information sciences and fuzzy logic.

Decision Making: Uncertainty, Imperfection, Deliberation and Scalability

Author : Tatiana V. Guy
Publisher : Springer
ISBN 13 : 3319151444
Total Pages : 193 pages
Book Rating : 4.3/5 (191 download)

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Book Synopsis Decision Making: Uncertainty, Imperfection, Deliberation and Scalability by : Tatiana V. Guy

Download or read book Decision Making: Uncertainty, Imperfection, Deliberation and Scalability written by Tatiana V. Guy and published by Springer. This book was released on 2015-02-09 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume focuses on uncovering the fundamental forces underlying dynamic decision making among multiple interacting, imperfect and selfish decision makers. The chapters are written by leading experts from different disciplines, all considering the many sources of imperfection in decision making, and always with an eye to decreasing the myriad discrepancies between theory and real world human decision making. Topics addressed include uncertainty, deliberation cost and the complexity arising from the inherent large computational scale of decision making in these systems. In particular, analyses and experiments are presented which concern: • task allocation to maximize “the wisdom of the crowd”; • design of a society of “edutainment” robots who account for one anothers’ emotional states; • recognizing and counteracting seemingly non-rational human decision making; • coping with extreme scale when learning causality in networks; • efficiently incorporating expert knowledge in personalized medicine; • the effects of personality on risky decision making. The volume is a valuable source for researchers, graduate students and practitioners in machine learning, stochastic control, robotics, and economics, among other fields.

COMPUTATIONAL INTELLIGENCE IN COMPLEX DECISION MAKING SYSTEMS

Author : Ruan Da
Publisher : Springer Science & Business Media
ISBN 13 : 9491216295
Total Pages : 398 pages
Book Rating : 4.4/5 (912 download)

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Book Synopsis COMPUTATIONAL INTELLIGENCE IN COMPLEX DECISION MAKING SYSTEMS by : Ruan Da

Download or read book COMPUTATIONAL INTELLIGENCE IN COMPLEX DECISION MAKING SYSTEMS written by Ruan Da and published by Springer Science & Business Media. This book was released on 2010-06-01 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, there has been a growing interest in the need for designing intelligent systems to address complex decision systems. One of the most challenging issues for the intelligent system is to effectively handle real-world uncertainties that cannot be eliminated. These uncertainties include various types of information that are incomplete, imprecise, fragmentary, not fully reliable, vague, contradictory, deficient, and overloading. The uncertainties result in a lack of the full and precise knowledge of the decision system, including the determining and selection of evaluation criteria, alternatives, weights, assignment scores, and the final integrated decision result. Computational intelligent techniques (including fuzzy logic, neural networks, and genetic algorithms etc.), which are complimentary to the existing traditional techniques, have shown great potential to solve these demanding, real-world decision problems that exist in uncertain and unpredictable environments. These technologies have formed the foundation for intelligent systems.

Computational Intelligence for Business Analytics

Author : Witold Pedrycz
Publisher : Springer Nature
ISBN 13 : 3030738191
Total Pages : 417 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Computational Intelligence for Business Analytics by : Witold Pedrycz

Download or read book Computational Intelligence for Business Analytics written by Witold Pedrycz and published by Springer Nature. This book was released on 2021-10-26 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: Corporate success has been changed by the importance of new developments in Business Analytics (BA) and furthermore by the support of computational intelligence- based techniques. This book opens a new avenues in these subjects, identifies key developments and opportunities. The book will be of interest for students, researchers and professionals to identify innovative ways delivered by Business Analytics based on computational intelligence solutions. They help elicit information, handle knowledge and support decision-making for more informed and reliable decisions even under high uncertainty environments.Computational Intelligence for Business Analytics has collected the latest technological innovations in the field of BA to improve business models related to Group Decision-Making, Forecasting, Risk Management, Knowledge Discovery, Data Breach Detection, Social Well-Being, among other key topics related to this field.

Applications of Artificial Intelligence for Decision-Making

Author : Patrick J Talbot
Publisher : CreateSpace
ISBN 13 : 9781502907592
Total Pages : 298 pages
Book Rating : 4.9/5 (75 download)

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Book Synopsis Applications of Artificial Intelligence for Decision-Making by : Patrick J Talbot

Download or read book Applications of Artificial Intelligence for Decision-Making written by Patrick J Talbot and published by CreateSpace. This book was released on 2015-04-10 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Book Description: We have the data! Too much data! Decision-making requires that data be filtered and refined to provide information. Adding context to the content produces actionable knowledge. Unfortunately, current techniques strip away the uncertainty associated with the raw data. This book provides a decision-centered approach for coping with uncertainty that combines what people do best with what computers do best. Algorithms "plug into"the knowledge base from a single import/export interface, facilitating multi-strategy reasoning. Triage filters the data, extraction of hedge words capture uncertainty, an executable knowledge base provides content in context, data fusion propagates uncertainty, data analytics discover patterns, and plan optimization tools move the decision-maker from "what's going on" to "what to do." Displays present actionable knowledge with associated uncertainties explicitly shown. Fifteen applications are shown ranging from longevity prediction, to a retail problem solver, to intelligence community applications, to starship cybernetics. We wrote the book to provide the practitioner with compelling ideas for orchestrating artificial intelligence, statistical, and mathematical algorithms to produce fully integrated decision support systems. Novel techniques of particular interest are: a knowledge representation that provides a unifying framework for multi-strategy reasoning and simulation, a robust treatment of uncertainty, monitor-assess-plan-execute decision loops for routine and quick-reaction decisions, eight techniques for automated discovery of unknown unknowns, level 4 (process refinement) data fusion, and a self-aware knowledge base that "knows what it knows."

Uncertainty in Artificial Intelligence

Author : David Heckerman
Publisher : Morgan Kaufmann
ISBN 13 : 1483214516
Total Pages : 554 pages
Book Rating : 4.4/5 (832 download)

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Book Synopsis Uncertainty in Artificial Intelligence by : David Heckerman

Download or read book Uncertainty in Artificial Intelligence written by David Heckerman and published by Morgan Kaufmann. This book was released on 2014-05-12 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty in Artificial Intelligence contains the proceedings of the Ninth Conference on Uncertainty in Artificial Intelligence held at the Catholic University of America in Washington, DC, on July 9-11, 1993. The papers focus on methods of reasoning and decision making under uncertainty as applied to problems in artificial intelligence (AI) and cover topics ranging from knowledge acquisition and automated model construction to learning, planning, temporal reasoning, and machine vision. Comprised of 66 chapters, this book begins with a discussion on causality in Bayesian belief networks before turning to a decision theoretic account of conditional ought statements that rectifies glaring deficiencies in classical deontic logic and forms a sound basis for qualitative decision theory. Subsequent chapters explore trade-offs in constructing and evaluating temporal influence diagrams; normative engineering risk management systems; additive belief-network models; and sensitivity analysis for probability assessments in Bayesian networks. Automated model construction and learning as well as algorithms for inference and decision making are also considered. This monograph will be of interest to both students and practitioners in the fields of AI and computer science.

Financial Decision Making Using Computational Intelligence

Author : Michael Doumpos
Publisher : Springer Science & Business Media
ISBN 13 : 1461437733
Total Pages : 336 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Financial Decision Making Using Computational Intelligence by : Michael Doumpos

Download or read book Financial Decision Making Using Computational Intelligence written by Michael Doumpos and published by Springer Science & Business Media. This book was released on 2012-07-23 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: The increasing complexity of financial problems and the enormous volume of financial data often make it difficult to apply traditional modeling and algorithmic procedures. In this context, the field of computational intelligence provides an arsenal of particularly useful techniques. These techniques include new modeling tools for decision making under risk and uncertainty, data mining techniques for analyzing complex data bases, and powerful algorithms for complex optimization problems. Computational intelligence has also evolved rapidly over the past few years and it is now one of the most active fields in operations research and computer science. This volume presents the recent advances of the use of computation intelligence in financial decision making. The book covers all the major areas of computational intelligence and a wide range of problems in finance, such as portfolio optimization, credit risk analysis, asset valuation, financial forecasting, and trading.

Computational Intelligence for Decision Support

Author : Zhengxin Chen
Publisher : CRC Press
ISBN 13 : 9781420049145
Total Pages : 408 pages
Book Rating : 4.0/5 (491 download)

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Book Synopsis Computational Intelligence for Decision Support by : Zhengxin Chen

Download or read book Computational Intelligence for Decision Support written by Zhengxin Chen and published by CRC Press. This book was released on 1999-11-24 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent decision support relies on techniques from a variety of disciplines, including artificial intelligence and database management systems. Most of the existing literature neglects the relationship between these disciplines. By integrating AI and DBMS, Computational Intelligence for Decision Support produces what other texts don't: an explanation of how to use AI and DBMS together to achieve high-level decision making. Threading relevant disciplines from both science and industry, the author approaches computational intelligence as the science developed for decision support. The use of computational intelligence for reasoning and DBMS for retrieval brings about a more active role for computational intelligence in decision support, and merges computational intelligence and DBMS. The introductory chapter on technical aspects makes the material accessible, with or without a decision support background. The examples illustrate the large number of applications and an annotated bibliography allows you to easily delve into subjects of greater interest. The integrated perspective creates a book that is, all at once, technical, comprehensible, and usable. Now, more than ever, it is important for science and business workers to creatively combine their knowledge to generate effective, fruitful decision support. Computational Intelligence for Decision Support makes this task manageable.

Advances in Computational Intelligence, Part I

Author : Salvatore Greco
Publisher : Springer
ISBN 13 : 364231709X
Total Pages : 674 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Advances in Computational Intelligence, Part I by : Salvatore Greco

Download or read book Advances in Computational Intelligence, Part I written by Salvatore Greco and published by Springer. This book was released on 2012-07-20 with total page 674 pages. Available in PDF, EPUB and Kindle. Book excerpt: These four volumes (CCIS 297, 298, 299, 300) constitute the proceedings of the 14th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2012, held in Catania, Italy, in July 2012. The 258 revised full papers presented together with six invited talks were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on fuzzy machine learning and on-line modeling; computing with words and decision making; soft computing in computer vision; rough sets and complex data analysis: theory and applications; intelligent databases and information system; information fusion systems; philosophical and methodological aspects of soft computing; basic issues in rough sets; 40th anniversary of the measures of fuziness; SPS11 uncertainty in profiling systems and applications; handling uncertainty with copulas; formal methods to deal with uncertainty of many-valued events; linguistic summarization and description of data; fuzzy implications: theory and applications; sensing and data mining for teaching and learning; theory and applications of intuitionistic fuzzy sets; approximate aspects of data mining and database analytics; fuzzy numbers and their applications; information processing and management of uncertainty in knowledge-based systems; aggregation functions; imprecise probabilities; probabilistic graphical models with imprecision: theory and applications; belief function theory: basics and/or applications; fuzzy uncertainty in economics and business; new trends in De Finetti's approach; fuzzy measures and integrals; multicriteria decision making; uncertainty in privacy and security; uncertainty in the spirit of Pietro Benvenuti; coopetition; game theory; probabilistic approach.

Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations

Author : Jesús Medina
Publisher : Springer
ISBN 13 : 3319914731
Total Pages : 835 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations by : Jesús Medina

Download or read book Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations written by Jesús Medina and published by Springer. This book was released on 2018-05-30 with total page 835 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three volume set (CCIS 853-855) constitutes the proceedings of the 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2017, held in Cádiz, Spain, in June 2018. The 193 revised full papers were carefully reviewed and selected from 383 submissions. The papers are organized in topical sections on advances on explainable artificial intelligence; aggregation operators, fuzzy metrics and applications; belief function theory and its applications; current techniques to model, process and describe time series; discrete models and computational intelligence; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy logic and artificial intelligence problems; fuzzy mathematical analysis and applications; fuzzy methods in data mining and knowledge discovery; fuzzy transforms: theory and applications to data analysis and image processing; imprecise probabilities: foundations and applications; mathematical fuzzy logic, mathematical morphology; measures of comparison and entropies for fuzzy sets and their extensions; new trends in data aggregation; pre-aggregation functions and generalized forms of monotonicity; rough and fuzzy similarity modelling tools; soft computing for decision making in uncertainty; soft computing in information retrieval and sentiment analysis; tri-partitions and uncertainty; decision making modeling and applications; logical methods in mining knowledge from big data; metaheuristics and machine learning; optimization models for modern analytics; uncertainty in medicine; uncertainty in Video/Image Processing (UVIP).

Decision Theory Models for Applications in Artificial Intelligence: Concepts and Solutions

Author : Sucar, L. Enrique
Publisher : IGI Global
ISBN 13 : 160960167X
Total Pages : 444 pages
Book Rating : 4.6/5 (96 download)

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Book Synopsis Decision Theory Models for Applications in Artificial Intelligence: Concepts and Solutions by : Sucar, L. Enrique

Download or read book Decision Theory Models for Applications in Artificial Intelligence: Concepts and Solutions written by Sucar, L. Enrique and published by IGI Global. This book was released on 2011-10-31 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the goals of artificial intelligence (AI) is creating autonomous agents that must make decisions based on uncertain and incomplete information. The goal is to design rational agents that must take the best action given the information available and their goals. Decision Theory Models for Applications in Artificial Intelligence: Concepts and Solutions provides an introduction to different types of decision theory techniques, including MDPs, POMDPs, Influence Diagrams, and Reinforcement Learning, and illustrates their application in artificial intelligence. This book provides insights into the advantages and challenges of using decision theory models for developing intelligent systems.

Advances in Computational Intelligence, Part IV

Author : Salvatore Greco
Publisher : Springer
ISBN 13 : 3642317243
Total Pages : 707 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Advances in Computational Intelligence, Part IV by : Salvatore Greco

Download or read book Advances in Computational Intelligence, Part IV written by Salvatore Greco and published by Springer. This book was released on 2012-07-23 with total page 707 pages. Available in PDF, EPUB and Kindle. Book excerpt: These four volumes (CCIS 297, 298, 299, 300) constitute the proceedings of the 14th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2012, held in Catania, Italy, in July 2012. The 258 revised full papers presented together with six invited talks were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on fuzzy machine learning and on-line modeling; computing with words and decision making; soft computing in computer vision; rough sets and complex data analysis: theory and applications; intelligent databases and information system; information fusion systems; philosophical and methodological aspects of soft computing; basic issues in rough sets; 40th anniversary of the measures of fuziness; SPS11 uncertainty in profiling systems and applications; handling uncertainty with copulas; formal methods to deal with uncertainty of many-valued events; linguistic summarization and description of data; fuzzy implications: theory and applications; sensing and data mining for teaching and learning; theory and applications of intuitionistic fuzzy sets; approximate aspects of data mining and database analytics; fuzzy numbers and their applications; information processing and management of uncertainty in knowledge-based systems; aggregation functions; imprecise probabilities; probabilistic graphical models with imprecision: theory and applications; belief function theory: basics and/or applications; fuzzy uncertainty in economics and business; new trends in De Finetti's approach; fuzzy measures and integrals; multi criteria decision making; uncertainty in privacy and security; uncertainty in the spirit of Pietro Benvenuti; coopetition; game theory; probabilistic approach.

Intelligent Decision and Policy Making Support Systems

Author : Da Ruan
Publisher : Springer
ISBN 13 : 3540783083
Total Pages : 320 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Intelligent Decision and Policy Making Support Systems by : Da Ruan

Download or read book Intelligent Decision and Policy Making Support Systems written by Da Ruan and published by Springer. This book was released on 2008-04-16 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited book reports recent research results and provides a state-of-the-art on intelligent decision support systems applications, lessons learned and future research directions. The book covers a balanced mixture of theory and practice, including new methods and developments of intelligent decision support systems applications in Society and Policy Support. Its main objective is to gather a peer-reviewed collection of high quality contributions in the relevant topic areas.

Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications

Author : Jesús Medina
Publisher : Springer
ISBN 13 : 3319914790
Total Pages : 773 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications by : Jesús Medina

Download or read book Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications written by Jesús Medina and published by Springer. This book was released on 2018-05-29 with total page 773 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three volume set (CCIS 853-855) constitutes the proceedings of the 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2017, held in Cádiz, Spain, in June 2018. The 193 revised full papers were carefully reviewed and selected from 383 submissions. The papers are organized in topical sections on advances on explainable artificial intelligence; aggregation operators, fuzzy metrics and applications; belief function theory and its applications; current techniques to model, process and describe time series; discrete models and computational intelligence; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy logic and artificial intelligence problems; fuzzy mathematical analysis and applications; fuzzy methods in data mining and knowledge discovery; fuzzy transforms: theory and applications to data analysis and image processing; imprecise probabilities: foundations and applications; mathematical fuzzy logic, mathematical morphology; measures of comparison and entropies for fuzzy sets and their extensions; new trends in data aggregation; pre-aggregation functions and generalized forms of monotonicity; rough and fuzzy similarity modelling tools; soft computing for decision making in uncertainty; soft computing in information retrieval and sentiment analysis; tri-partitions and uncertainty; decision making modeling and applications; logical methods in mining knowledge from big data; metaheuristics and machine learning; optimization models for modern analytics; uncertainty in medicine; uncertainty in Video/Image Processing (UVIP).