This is the first book that integrates nonmonotonic reasoning and belief change into a single framework from an artificial intelligence logic point-of-view. The approach to both these subjects is based on a powerful notion of an epistemic state that subsumes both existing models for nonmonotonic inference and current models for belief change. Many results and constructions in the book are completely new and have not appeared earlier in the literature.

This book constitutes the refereed proceedings of the 18th International Symposium on Methodologies for Intelligent Systems, ISMIS 2009, held in Prague, Czech Republic, in September 2009. The 60 revised papers presented together with 4 plenary talks were carefully reviewed and selected from over 111 submissions. The papers are organized in topical sections on knowledge discovery and data mining, applications and intelligent systems in Medicine, logical and theoretical aspects of intelligent systems, text mining, applications of intelligent sysems in music, information processing, agents, machine learning, applications of intelligent systems, complex data, general AI as well as uncertainty.

We are happy to present the first volume of the Handbook of Defeasible Reasoning and Uncertainty Management Systems. Uncertainty pervades the real world and must therefore be addressed by every system that attempts to represent reality. The representation of uncertainty is a ma jor concern of philosophers, logicians, artificial intelligence researchers and com puter sciencists, psychologists, statisticians, economists and engineers. The present Handbook volumes provide frontline coverage of this area. This Handbook was produced in the style of previous handbook series like the Handbook of Philosoph ical Logic, the Handbook of Logic in Computer Science, the Handbook of Logic in Artificial Intelligence and Logic Programming, and can be seen as a companion to them in covering the wide applications of logic and reasoning. We hope it will answer the needs for adequate representations of uncertainty. This Handbook series grew out of the ESPRIT Basic Research Project DRUMS II, where the acronym is made out of the Handbook series title. This project was financially supported by the European Union and regroups 20 major European research teams working in the general domain of uncertainty. As a fringe benefit of the DRUMS project, the research community was able to create this Hand book series, relying on the DRUMS participants as the core of the authors for the Handbook together with external international experts.

The Second Edition of this text continues to provide a comprehensive introduction to Logic, a subject that is increasingly becoming popular among students. What distinguishes the text is its graded step-by-step approach to the subject, with informal logic forming the basis and Symbolic logic and Inductive logic forming the more advanced steps. The book also uses a hands-on approach to teaching of logic to induce self-learning, as shown in sections such as on how to create a truth table or a truth tree, on providing strategic tips for formal derivations, and on how to approach symbolization in predicate logic. The Appendices, including those on Indian logic and the nature of inference in Indian logic, are designed to create greater awareness about the extent and depth of the field among students. WHAT’S NEW TO THIS EDITION  A new Appendix on Basic Set Theory. It covers all the fundamental concepts, principles and operations in Basic Set Theory.  Some sections in Chapter 3 on Fallacies have been modified.  Corrections/Modifications done wherever required. KEY FEATURES  In-depth and extensive coverage of Predicate logic.  Covers both Informal and Formal logic.  Each section has many worked-out examples and exercises.  Worked-out examples given in a step-by-step manner for easy compre-hension.  Keywords at the end of each chapter. Intended primarily as a text for students of Philosophy, the book would also be useful to students of Mathematics, Computer Science and Engineering where Logic is offered as part of their course. Read More

We are happy to present the second volume of the Handbook of Defeasible Reasoning and Uncertainty Management Systems. Uncertainty pervades the real world and must therefore be addressed by every system that attempts to represent reality. The representation of un certainty is a major concern of philosophers, logicians, artificial intelligence researchers and computer sciencists, psychologists, statisticians, economists and engineers. The present Handbook volumes provide frontline coverage of this area. This Handbook was produced in the style of previous handbook series like the Handbook of Philosophical Logic, the Handbook of Logic in Computer Science, the Handbook of Logic in Artificial Intelligence and Logic Programming, and can be seen as a companion to them in covering the wide applications of logic and reasoning. We hope it will answer the needs for adequate representations of uncertainty. This Handbook series grew out of the ESPRIT Basic Research Project DRUMS II, where the acronym is made out of the Handbook series title. This project was financially supported by the European Union and regroups 20 major European research teams working in the general domain of uncer tainty. As a fringe benefit of the DRUMS project, the research community was able to create this Handbook series, relying on the DRUMS partici pants as the core of the authors for the Handbook together with external international experts.

Inconsistency arises in many areas in advanced computing. Often inconsistency is unwanted, for example in the specification for a plan or in sensor fusion in robotics; however, sometimes inconsistency is useful. Whether inconsistency is unwanted or useful, there is a need to develop tolerance to inconsistency in application technologies such as databases, knowledge bases, and software systems. To address this situation, inconsistency tolerance is being built on foundational technologies for identifying and analyzing inconsistency in information, for representing and reasoning with inconsistent information, for resolving inconsistent information, and for merging inconsistent information. The idea for this book arose out of a Dagstuhl Seminar on the topic held in summer 2003. The nine chapters in this first book devoted to the subject of inconsistency tolerance were carefully invited and anonymously reviewed. The book provides an exciting introduction to this new field.

The Handbook of Modal Logic contains 20 articles, which collectively introduce contemporary modal logic, survey current research, and indicate the way in which the field is developing. The articles survey the field from a wide variety of perspectives: the underling theory is explored in depth, modern computational approaches are treated, and six major applications areas of modal logic (in Mathematics, Computer Science, Artificial Intelligence, Linguistics, Game Theory, and Philosophy) are surveyed. The book contains both well-written expository articles, suitable for beginners approaching the subject for the first time, and advanced articles, which will help those already familiar with the field to deepen their expertise. Please visit: http://people.uleth.ca/~woods/RedSeriesPromo_WP/PubSLPR.html - Compact modal logic reference - Computational approaches fully discussed - Contemporary applications of modal logic covered in depth