This book discusses current topics in rough set theory. Since Pawlak’s rough set theory was first proposed to offer a basis for imprecise and uncertain data and reasoning from data, many workers have investigated its foundations and applications. Examining various topical issues, including object-oriented rough set models, recommendation systems, decision tables, and granular computing, the book is a valuable resource for students and researchers in the field.
This book explores reasoning with rough sets by developing a granularity-based framework. It begins with a brief description of the rough set theory, then examines selected relations between rough set theory and non-classical logics including modal logic. In addition, it develops a granularity-based framework for reasoning in which various types of reasoning can be formalized. The book will be of interest to all researchers whose work involves Artificial Intelligence, databases and/or logic.
A quantum computer is a computer based on a computational model which uses quantum mechanics, which is a subfield of physics to study phenomena at the micro level. There has been a growing interest on quantum computing in the 1990's and some quantum computers at the experimental level were recently implemented. Quantum computers enable super-speed computation and can solve some important problems whose solutions were regarded impossible or intractable with traditional computers. This book provides a quick introduction to quantum computing for readers who have no backgrounds of both theory of computation and quantum mechanics. “Elements of Quantum Computing” presents the history, theories and engineering applications of quantum computing. The book is suitable to computer scientists, physicists and software engineers.
This book approaches to the subject of common-sense reasoning in AI using epistemic situation calculus which integrates the ideas of situation calculus and epistemic logic. Artificial intelligence (AI) is the research area of science and engineering for intelligent machines, especially intelligent computer programs. It is very important to deal with common-sense reasoning in knowledge-based systems. If we employ a logic-based framework, classical logic is not suited for the purpose of describing common-sense reasoning. It is well known that there are several difficulties with logic-based approaches, e.g., the so-called Fame Problem. We try to formalize common-sense reasoning in the context of granular computing based on rough set theory. The book is intended for those, like experts and students, who wish to get involved in the field as a monograph or a textbook for the subject. We assume that the reader has mastered the material ordinarily covered in AI and mathematical logic
This book is written as an introduction to annotated logics. It provides logical foundations for annotated logics, discusses some interesting applications of these logics and also includes the authors' contributions to annotated logics. The central idea of the book is to show how annotated logic can be applied as a tool to solve problems of technology and of applied science. The book will be of interest to pure and applied logicians, philosophers and computer scientists as a monograph on a kind of paraconsistent logic. But, the layman will also take profit from its reading.
This book approaches to the subject of common-sense reasoning in AI using epistemic situation calculus which integrates the ideas of situation calculus and epistemic logic. Artificial intelligence (AI) is the research area of science and engineering for intelligent machines, especially intelligent computer programs. It is very important to deal with common-sense reasoning in knowledge-based systems. If we employ a logic-based framework, classical logic is not suited for the purpose of describing common-sense reasoning. It is well known that there are several difficulties with logic-based approaches, e.g., the so-called Fame Problem. We try to formalize common-sense reasoning in the context of granular computing based on rough set theory. The book is intended for those, like experts and students, who wish to get involved in the field as a monograph or a textbook for the subject. We assume that the reader has mastered the material ordinarily covered in AI and mathematical logic
This book is written as an introduction to annotated logics. It provides logical foundations for annotated logics, discusses some interesting applications of these logics and also includes the authors' contributions to annotated logics. The central idea of the book is to show how annotated logic can be applied as a tool to solve problems of technology and of applied science. The book will be of interest to pure and applied logicians, philosophers and computer scientists as a monograph on a kind of paraconsistent logic. But, the layman will also take profit from its reading.
This book discusses current topics in rough set theory. Since Pawlak’s rough set theory was first proposed to offer a basis for imprecise and uncertain data and reasoning from data, many workers have investigated its foundations and applications. Examining various topical issues, including object-oriented rough set models, recommendation systems, decision tables, and granular computing, the book is a valuable resource for students and researchers in the field.
This book explores reasoning with rough sets by developing a granularity-based framework. It begins with a brief description of the rough set theory, then examines selected relations between rough set theory and non-classical logics including modal logic. In addition, it develops a granularity-based framework for reasoning in which various types of reasoning can be formalized. The book will be of interest to all researchers whose work involves Artificial Intelligence, databases and/or logic.
This will help us customize your experience to showcase the most relevant content to your age group
Please select from below
Login
Not registered?
Sign up
Already registered?
Success – Your message will goes here
We'd love to hear from you!
Thank you for visiting our website. Would you like to provide feedback on how we could improve your experience?
This site does not use any third party cookies with one exception — it uses cookies from Google to deliver its services and to analyze traffic.Learn More.