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Artificial intelligence --- Logic, Symbolic and mathematical

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Machine learning is widely used for data analysis. Dynamic fuzzy data are one of the most difficult types of data to analyse in the field of big data, cloud computing, the Internet of Things, and quantum information. At present, the processing of this kind of data is not very mature. The authors carried out more than 20 years of research, and show in this book their most important results. The seven chapters of the book are devoted to key topics such as dynamic fuzzy machine learning models, dynamic fuzzy self-learning subspace algorithms, fuzzy decision tree learning, dynamic concepts based on dynamic fuzzy sets, semi-supervised multi-task learning based on dynamic fuzzy data, dynamic fuzzy hierarchy learning, examination of multi-agent learning model based on dynamic fuzzy logic. This book can be used as a reference book for senior college students and graduate students as well as college teachers and scientific and technical personnel involved in computer science, artificial intelligence, machine learning, automation, data analysis, mathematics, management, cognitive science, and finance. It can be also used as the basis for teaching the principles of dynamic fuzzy learning.

Fuzzy logic. --- Nonlinear logic --- Fuzzy mathematics --- Logic, Symbolic and mathematical --- Fuzzy systems

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Computer logic. --- Computer logic --- Study and teaching. --- Computer science logic --- Logic, Symbolic and mathematical

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This book constitutes selected papers from the 12th International Workshop on Rewriting Logic and Its Applications, WRLA 2020, held in Dublin, Ireland, in April 2020. Due to the COVID-19 pandemic the workshop took place virtually. The 11 full papers presented in this volume were carefully reviewed and selected from 16 submissions Rewriting logic is a natural model of computation and an expressive semantic framework for concurrency, parallelism, communication, and interaction. It can be used for specifying a wide range of systems and languages in various application fields.

Computer logic. --- Logics and Meanings of Programs. --- Computer science logic --- Logic, Symbolic and mathematical --- Computer science. --- Computer Science Logic and Foundations of Programming. --- Informatics --- Science

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The contributions in this book survey results on combinations of probabilistic and various other classical, temporal and justification logical systems. Formal languages of these logics are extended with probabilistic operators. The aim is to provide a systematic overview and an accessible presentation of mathematical techniques used to obtain results on formalization, completeness, compactness and decidability. The book will be of value to researchers in logic and it can be used as a supplementary text in graduate courses on non-classical logics.

Computer logic. --- Probabilities. --- Mathematical logic. --- Logics and Meanings of Programs. --- Probability Theory and Stochastic Processes. --- Mathematical Logic and Foundations. --- Algebra of logic --- Logic, Universal --- Mathematical logic --- Symbolic and mathematical logic --- Symbolic logic --- Mathematics --- Algebra, Abstract --- Metamathematics --- Set theory --- Syllogism --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Mathematical statistics --- Risk --- Computer science logic --- Logic, Symbolic and mathematical --- Computer logic, Probabilities, Logic, Symbolic and mathematical.