Commonsense Reasoning

To endow computers with common sense is one of the major long-term goals of Artificial Intelligence research. One approach to this problem is to formalize commonsense reasoning using mathematical logic. Commonsense Reasoning is a detailed, high-level reference on logic-based commonsense reasoning. It uses the event calculus, a highly powerful and usable tool for commonsense reasoning, which Erik T. Mueller demonstrates as the most effective tool for the broadest range of applications. He provides an up-to-date work promoting the use of the event calculus for commonsense reasoning, and bringing into one place information scattered across many books and papers. Mueller shares the knowledge gained in using the event calculus and extends the literature with detailed event calculus solutions to problems that span many areas of the commonsense world. Covers key areas of commonsense reasoning including action, change, defaults, space, and mental states. The first full book on commonsense reasoning to use the event calculus. Contextualizes the event calculus within the framework of commonsense reasoning, introducing the event calculus as the best method overall. Focuses on how to use the event calculus formalism to perform commonsense reasoning, while existing papers and books examine the formalisms themselves. Includes fully worked out proofs and circumscriptions for every example.

While common sense and rationality often have been viewed as two distinct features in a unitifed cognitive map, this this volume offers novel, even paradoxical views of the relationship. Touching on various disciplines, it considers what constitutes human rationality, behavior, and intelligence.

While common sense and rationality have often been viewed as two distinct features in a unified cognitive map, this volume engages with this notion and comes up with novel and often paradoxical views of this relationship.

This book suggests that classification is a key to human commonsense reasoning and transforms traditional considerations of data and knowledge communications, presenting an effective classification of logical rules used in the modeling of commonsense reasoning.

"This book analyzes and compares the existing and most effective algorithms for mining through logical rules and shows how these approaches use shared concepts for mining logical rules, including item, item set, transaction, frequent itemset, maximal itemset, generator (non-redundant or irredundant itemset), closed itemset, support, and confidence"--

This book constitutes the proceedings of the 12th International Symposium on Automated Technology for Verification and Analysis, ATVA 2014, held in Sydney, Australia, in November 2014. The 29 revised papers presented in this volume were carefully reviewed and selected from 76 submissions. They show current research on theoretical and practical aspects of automated analysis, verification and synthesis by providing an international forum for interaction among the researchers in academia and industry.

The three-volume set LNAI 3213, LNAI 3214, and LNAI 3215 constitutes the refereed proceedings of the 8th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2004, held in Wellington, New Zealand in September 2004. The over 450 papers presented were carefully reviewed and selected from numerous submissions. The papers present a wealth of original research results from the field of intelligent information processing in the broadest sense; among the areas covered are artificial intelligence, computational intelligence, cognitive technologies, soft computing, data mining, knowledge processing, various new paradigms in biologically inspired computing, and applications in various domains like bioinformatics, finance, signal processing etc.

Representations of Commonsense Knowledge provides a rich language for expressing commonsense knowledge and inference techniques for carrying out commonsense knowledge. This book provides a survey of the research on commonsense knowledge. Organized into 10 chapters, this book begins with an overview of the basic ideas on artificial intelligence commonsense reasoning. This text then examines the structure of logic, which is roughly analogous to that of a programming language. Other chapters describe how rules of universal validity can be applied to facts known with absolute certainty to deduce other facts known with absolute certainty. This book discusses as well some prominent issues in plausible inference. The final chapter deals with commonsense knowledge about the interrelations and interactions among agents and discusses some issues in human and social interactions that have been studied in the artificial intelligence literature. This book is a valuable resource for students on a graduate course on knowledge representation.