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A broad introduction to the subject; many exercises with full solutions are provided.
This volume offers the reader a systematic and throughout account of branches of logic instrumental for computer science, data science and artificial intelligence. Addressed in it are propositional, predicate, modal, epistemic, dynamic, temporal logics as well as applicable in data science many-valued logics and logics of concepts (rough logics). It offers a look into second-order logics and approximate logics of parts. The book concludes with appendices on set theory, algebraic structures, computability, complexity, MV-algebras and transition systems, automata and formal grammars. By this composition of the text, the reader obtains a self-contained exposition that can serve as the textbook on logics and relevant disciplines as well as a reference text.
Modal logics, originally conceived in philosophy, have recently found many applications in computer science, artificial intelligence, the foundations of mathematics, linguistics and other disciplines. Celebrated for their good computational behaviour, modal logics are used as effective formalisms for talking about time, space, knowledge, beliefs, actions, obligations, provability, etc. However, the nice computational properties can drastically change if we combine some of these formalisms into a many-dimensional system, say, to reason about knowledge bases developing in time or moving objects.To study the computational behaviour of many-dimensional modal logics is the main aim of this book. On the one hand, it is concerned with providing a solid mathematical foundation for this discipline, while on the other hand, it shows that many seemingly different applied many-dimensional systems (e.g., multi-agent systems, description logics with epistemic, temporal and dynamic operators, spatio-temporal logics, etc.) fit in perfectly with this theoretical framework, and so their computational behaviour can be analyzed using the developed machinery.We start with concrete examples of applied one- and many-dimensional modal logics such as temporal, epistemic, dynamic, description, spatial logics, and various combinations of these. Then we develop a mathematical theory for handling a spectrum of 'abstract' combinations of modal logics - fusions and products of modal logics, fragments of first-order modal and temporal logics - focusing on three major problems: decidability, axiomatizability, and computational complexity. Besides the standard methods of modal logic, the technical toolkit includes the method of quasimodels, mosaics, tilings, reductions to monadic second-order logic, algebraic logic techniques. Finally, we apply the developed machinery and obtained results to three case studies from the field of knowledge representation and reasoning: temporal epistemic logics for reasoning about multi-agent systems, modalized description logics for dynamic ontologies, and spatio-temporal logics.The genre of the book can be defined as a research monograph. It brings the reader to the front line of current research in the field by showing both recent achievements and directions of future investigations (in particular, multiple open problems). On the other hand, well-known results from modal and first-order logic are formulated without proofs and supplied with references to accessible sources.The intended audience of this book is logicians as well as those researchers who use logic in computer science and artificial intelligence. More specific application areas are, e.g., knowledge representation and reasoning, in particular, terminological, temporal and spatial reasoning, or reasoning about agents. And we also believe that researchers from certain other disciplines, say, temporal and spatial databases or geographical information systems, will benefit from this book as well.Key Features:• Integrated approach to modern modal and temporal logics and their applications in artificial intelligence and computer science• Written by internationally leading researchers in the field of pure and applied logic• Combines mathematical theory of modal logic and applications in artificial intelligence and computer science• Numerous open problems for further research• Well illustrated with pictures and tables
Dynamic Epistemic Logic is the logic of knowledge change. This book provides various logics to support such formal specifications, including proof systems. Concrete examples and epistemic puzzles enliven the exposition. The book also offers exercises with answers. It is suitable for graduate courses in logic. Many examples, exercises, and thorough completeness proofs and expressivity results are included. A companion web page offers slides for lecturers and exams for further practice.
This book constitutes the proceedings of the 17th European Conference on Logics in Artificial Intelligence, JELIA 2021, held as a virtual event, in May 2021. The 27 full papers and 3 short papers included in this volume were carefully reviewed and selected from 68 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).
Epistemic logic and, more generally, logics of knowledge and belief, originated with philosophers such as Jaakko Hintikka and David Lewis in the early 1960s. Since then, such logics have played a significant role not only in philosophy, but also in computer science, artificial intelligence, and economics. This handbook reports significant progress in a field that, while more mature, continues to be very active. This book should make it easier for new researchers to enter the field, and give experts a chance to appreciate work in related areas. The book starts with a gentle introduction to the logics of knowledge and belief; it gives an overview of the area and the material covered in the book. The following eleven chapters, each written by a leading researcher (or researchers), cover the topics of only knowing, awareness, knowledge and probability, knowledge and time, the dynamics of knowledge and of belief, model checking, game theory, agency, knowledge and ability, and security protocols. The chapters have been written so that they can be read independently and in any order. Each chapter ends with a section of notes that provides some historical background, including references, and a detailed bibliography.
This book provides an analysis of the meeting point between mainstream and formal theories of knowledge.
Develops a new logic paradigm which emphasizes evidence tracking, including theory, connections to other fields, and sample applications.
This is an advanced 2001 textbook on modal logic, a field which caught the attention of computer scientists in the late 1970s. Researchers in areas ranging from economics to computational linguistics have since realised its worth. The book is for novices and for more experienced readers, with two distinct tracks clearly signposted at the start of each chapter. The development is mathematical; prior acquaintance with first-order logic and its semantics is assumed, and familiarity with the basic mathematical notions of set theory is required. The authors focus on the use of modal languages as tools to analyze the properties of relational structures, including their algorithmic and algebraic aspects, and applications to issues in logic and computer science such as completeness, computability and complexity are considered. Three appendices supply basic background information and numerous exercises are provided. Ideal for anyone wanting to learn modern modal logic.
This introduction to the basic ideas of structural proof theory contains a thorough discussion and comparison of various types of formalization of first-order logic. Examples are given of several areas of application, namely: the metamathematics of pure first-order logic (intuitionistic as well as classical); the theory of logic programming; category theory; modal logic; linear logic; first-order arithmetic and second-order logic. In each case the aim is to illustrate the methods in relatively simple situations and then apply them elsewhere in much more complex settings. There are numerous exercises throughout the text. In general, the only prerequisite is a standard course in first-order logic, making the book ideal for graduate students and beginning researchers in mathematical logic, theoretical computer science and artificial intelligence. For the new edition, many sections have been rewritten to improve clarity, new sections have been added on cut elimination, and solutions to selected exercises have been included.