Difference Between Monotonic And Nonmonotonic Reasoning In Ai
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Nonmonotonic Reasoning
The publication of the seminal special issue on nonmonotonic logics by the Artificial Intelligence Journal in 1980 resulted in a new area of research in knowledge representation and changed the mainstream paradigm of logic that originated in antiquity. It led to discoveries of connections between logic, knowledge representation and computation, and attracted not only computer scientists but also logicians, mathematicians and philosophers. Nonmonotonic reasoning concerns situations when information is incomplete or uncertain. Thus, conclusions drawn lack iron-clad certainty that comes with classical logic reasoning. New information, even if the original one is retained, may change conclusions. Formal ways to capture mechanisms involved in nonmonotonic reasoning, and to exploit them for computation as in the answer set programming paradigm are at the heart of this research area. The conference NonMon@30 - Thirty Years of Nonmonotonic Reasoning, held in Lexington, KY, USA, October 22-25, 2010, aimed to sum up the experience of the first 30 years of nonmonotonic logics and to map paths into the future. It comprised eighteen invited talks and several technical presentations. The present volume consists of the texts based on twelve of the invited presentations. These papers offer unique insights into the key questions that have been driving the development of nonmonotonic reasoning and suggest problems worthy of consideration in the future. They paint the picture of the field that has a well-established tradition, and remains vibrant and relevant to long-term goals of artificial intelligence.
A Logical Theory of Nonmonotonic Inference and Belief Change
Author: Alexander Bochman
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-03-14
The main subject and objective of this book are logical foundations of non monotonic reasoning. This bears a presumption that there is such a thing as a general theory of non monotonic reasoning, as opposed to a bunch of systems for such a reasoning existing in the literature. It also presumes that this kind of reasoning can be analyzed by logical tools (broadly understood), just as any other kind of reasoning. In order to achieve our goal, we will provide a common logical basis and semantic representation in which different kinds of non monotonic reasoning can be interpreted and studied. The suggested framework will subsume ba sic forms of nonmonotonic inference, including not only the usual skeptical one, but also various forms of credulous (brave) and defeasible reasoning, as well as some new kinds such as contraction inference relations that express relative independence of pieces of data. In addition, the same framework will serve as a basis for a general theory of belief change which, among other things, will allow us to unify the main approaches to belief change existing in the literature, as well as to provide a constructive view of the semantic representation used. This book is a monograph rather than a textbook, with all its advantages (mainly for the author) and shortcomings (for the reader).
Nonmonotonic Logic
Author: V. Wiktor Marek
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-03-14
When I first participated in exploring theories of nonmonotonic reasoning in the late 1970s, I had no idea of the wealth of conceptual and mathematical results that would emerge from those halting first steps. This book by Wiktor Marek and Miroslaw Truszczynski is an elegant treatment of a large body of these results. It provides the first comprehensive treatment of two influen tial nonmonotonic logics - autoepistemic and default logic - and describes a number of surprising and deep unifying relationships between them. It also relates them to various modal logics studied in the philosophical logic litera ture, and provides a thorough treatment of their applications as foundations for logic programming semantics and for truth maintenance systems. It is particularly appropriate that Marek and Truszczynski should have authored this book, since so much of the research that went into these results is due to them. Both authors were trained in the Polish school of logic and they bring to their research and writing the logical insights and sophisticated mathematics that one would expect from such a background. I believe that this book is a splendid example of the intellectual maturity of the field of artificial intelligence, and that it will provide a model of scholarship for us all for many years to come. Ray Reiter Department of Computer Science University of Toronto Toronto, Canada M5S 1A4 and The Canadian Institute for Advanced Research Table of Contents 1 1 Introduction .........