The Handbook of Defeasible Reasoning and Uncertainty Management Systems is unique in its masterly survey of the computational and algorithmic problems of systems of applied reasoning. The various theoretical and modelling aspects of defeasible reasoning were dealt with in the first four volumes, and Volume 5 now turns to the algorithmic aspect. Topics covered include: Computation in valuation algebras; consequence finding algorithms; possibilistic logic; probabilistic argumentation systems, networks and satisfiability; algorithms for imprecise probabilities, for Dempster-Shafer, and network based decisions.

The Handbook of Logic in Artificial Intelligence and Logic Programming is a multi-volume work covering all major areas of the application of logic to artificial intelligence and logic programming. The authors are chosen on an international basis and are leaders in the fields covered. Volume 5 is the last in this well-regarded series. Logic is now widely recognized as one of the foundational disciplines of computing. It has found applications in virtually all aspects of the subject, from software and hardware engineering to programming languages and artificial intelligence. In response to the growing need for an in-depth survey of these applications the Handbook of Logic in Artificial Intelligence and its companion, the Handbook of Logic in Computer Science have been created. The Handbooks are a combination of authoritative exposition, comprehensive survey, and fundamental research exploring the underlying themes in the various areas. Some mathematical background is assumed, and much of the material will be of interest to logicians and mathematicians. Volume 5 focuses particularly on logic programming. The chapters, which in many cases are of monograph length and scope, emphasize possible unifying themes.

Development and environment problems have reached such alarming proportions that the very survival of humanity is now subject to critical and unprecedented threats. In its latest report, the German Advisory Council on Global Change (WBGU) criticizes Germany's global change research community for its lack of international orientation, its bias towards individual disciplines and for its weaknesses in translating scientific results into a form readily accessible to policymakers. The Council identifies alternatives for restructuring the research landscape, focusing primarily on a new 'Syndrome Approach' for global change research. By applying this tool, scientists can systematically describe and analyze the 'diseases' afflicting the Earth System, and thus elaborate response options.

Nonmonotonic reasoning provides formal methods that enable intelligent systems to operate adequately when faced with incomplete or changing information. In particular, it provides rigorous mechanisms for taking back conclusions that, in the presence of new information, turn out to be wrong and for deriving new, alternative conclusions instead. Nonmonotonic reasoning methods provide rigor similar to that of classical reasoning; they form a base for validation and verification and therefore increase confidence in intelligent systems that work with incomplete and changing information. Following a brief introduction to the concepts of predicate logic that are needed in the subsequent chapters, this book presents an in depth treatment of default logic. Other subjects covered include the major approaches of autoepistemic logic and circumscription, belief revision and its relationship to nonmonotonic inference, and briefly, the stable and well-founded semantics of logic programs.

Handbook of Automated Reasoning.

The capability to reason in a world full of uncertainties, vagueness and ignorance is what distinguishes humans. This ability to argument in a partially known world is the informal definition of common-sense reasoning. The question how common-sense reasoning is performed occupied humanity since we can think of. Last century this issue reached an immense importance. Especially during the last three decades the study of common-sense reasoning became one of the major research topics in Artificial Intelligence (AI). Several formalisms to capture the mechanism of common-sense reasoning have been proposed so far. This book concentrates on presenting the most important formalisms for common-sense reasoning, and, showing that one of the discussed formalisms serves perfectly to capture the mechanism of common-sense reasoning, since this formalism subsumes all other in this book introduced formalisms dealing with common-sense reasoning.