Qualitative Reasoning

Qualitative models are better able than traditional models to express states of incomplete knowledge about continuous mechanisms. Qualitative simulation guarantees to find all possible behaviors consistent with the knowledge in the model. This expressive power and coverage is important in problem solving for diagnosis, design, monitoring, explanation, and other applications of artificial intelligence.

The ability to reason qualitatively about physical systems is important to understanding and interacting with the world for both humans and intelligent machines. Accordingly, this study has become an important subject of research in the artificial intelligence and cognitive science communities. The goal of "qualitative physics," as the field is sometimes known, is to capture both the commonsense knowledge of the person on the street and the tacit knowledge underlying the quantitative knowledge used by engineers and scientists. "Readings in Qualitative Reasoning About Physical Systems" is an introduction and source book for this dynamic area, presenting reprints of key papers chosen by the editors and a group of expert referees. The editors present introductions discussing the context and significance of each group of articles as well as providing pointers to the rest of the literature. In addition, the volume includes several original papers that are not available elsewhere.

The book provides a survey about the field of Qualitative Reasoning, it contrasts and classifies its approaches and puts them into a common framework. Qualitative Reasoning represents an approach of Artificial Intelligence to model dynamic systems, about which little information is available, and to derive statements about the potential behavior of these systems, putting emphasis on a causal explanation of the behavior. Both variables and relationships between variables are described by means of qualitative terms such as small and large or positive and negative. Since this approach also takes into consideration the way how humans reason about physical systems, it can be stated that Qualitative Reasoning participates in the creation of a cognitive theory of non-numerical process descriptions which can be mapped onto a digital computer. This approach can be used for simulation, diagnosis, design, structure identification and interpretation. Areas of application are physics, medicine, the field of ecology, process control, etc. In addition to the classification of existing methods, the book presents a new approach based on fuzzy sets. And the work relates Qualitative Reasoning with such fields of Expert Systems, System Theory and Cognitive Science.

This book is a collection of some of the papers that were presented during a NATO Advanced Research Workshop (ARW) on "Intelligent Systems: Safety, Reliability and Maintainability Issues" that was held in Kusadasi, Turkey during August 24- 28, 1992. Attendance at this workshop was mainly by invitation only, drawing people internationally representing industry, government and the academic community. Many of the participants were internationally recognized leaders in the topic of the workshop. The purpose of the ARW was to bring together a highly distinguished group of people with the express purpose of debating where the issues of safety, reliability and maintainability place direct and tangible constraints on the development of intelligent systems. As a consequence, one of the major debating points in the ARW was the definition of intelligence, intelligent behaviour and their relation to complex dynamic systems. Two major conclusions evolved from the ARW are: 1. A continued need exists to develop formal, theoretical frameworks for the architecture of such systems, together with a reflection on the concept of intelligence. 2. There is a need to focus greater attention to the role that the human play in controlling intelligent systems. The workshop began by considering the typical features of an intelligent system. The complexity associated with multi-resolutional architectures was then discussed, leading to the identification of a necessity for the use of a combinatorial synthesis/approach. This was followed by a session on human interface issues.

The book focuses on original approaches intended to support the development of biologically inspired cognitive architectures. It bridges together different disciplines, including artificial intelligence, linguistics, neuro- and social sciences, psychology and philosophy of mind, among others. The chapters are based on contributions presented at the 12th Annual Meeting of the BICA Society (BICA 2021), which consisted of two parallel virtual events: Information in Biologically Inspired Cognitive Architectures based Systems, held during the 2021 Summit of the International Society for the Study of Information, on September 12-19, 2021, from Vienna, Austria, and the 2021 International Workshop on Biologically Inspired Cognitive Architectures, held during the 21st ACM International Conference on Intelligent Virtual Agents, on September 14-17, 2021, from the Fukuchiyama City, Kyoto, Japan. The book discusses emerging methods, theories and ideas towards the realization of general-purpose humanlike artificial intelligence or fostering a better understanding of the ways the human mind works. It provides engineers, mathematicians, psychologists, computer scientists and other experts with a timely snapshot of recent research and a source of inspiration for future developments in the broadly intended areas of artificial intelligence and biological inspiration.

Business modelling is a vast arena of research and practice, which is gaining increasing important in the rapid development of e-commerce, globalization, and in particular, the movement toward global e-business. The ability to utilize advanced computing technology to model, analyse and simulate various aspects of ever-changing businesses has made a significant impact on the way businesses are designed and run these days. With the current global e-business and e-commerce initiatives, it has become important that all businesses carefully validate their business objectives, requirements, and strategies through a careful process of formal business modelling. It is important for effective enterprise decision making to have clear, concise business models that allow the extraction of critical value from business processes and specify the rules to be globally enforced. Particularly in e-business specifications, the need to be unambiguous, accurate, and complete becomes even greater, because there may be no human mediator or agent to rely on in complex or unforeseen situations. Business Modelling: Multidisciplinary Approaches - Economics, Operational, and Information Systems Perspectives, arranged in three parts, brings scholarly perspectives from various disciplines to bear on some of the critical aspects of business modeling. The first part (chapters 1-8) focuses on business modelling fundamentals and starts with a series of economics and operations research perspectives. The second part (chapters 9-19) concentrates on modelling in electronic businesses and focuses on Management Information Systems and Decision Support Systems. The third part (chapters 20-22) centers on multidisciplinary business modelling progress, in particular on the seminal work of Professor Andrew B. Whinston.

Fully revised and updated, this third edition includes three new chapters on neural networks and deep learning including generative AI, causality, and the social, ethical and regulatory impacts of artificial intelligence. All parts have been updated with the methods that have been proven to work. The book's novel agent design space provides a coherent framework for learning, reasoning and decision making. Numerous realistic applications and examples facilitate student understanding. Every concept or algorithm is presented in pseudocode and open source AIPython code, enabling students to experiment with and build on the implementations. Five larger case studies are developed throughout the book and connect the design approaches to the applications. Each chapter now has a social impact section, enabling students to understand the impact of the various techniques as they learn them. An invaluable teaching package for undergraduate and graduate AI courses, this comprehensive textbook is accompanied by lecture slides, solutions, and code.

This book constitutes the refereed proceedings of the 10th International Conference on Spatial Information Theory, COSIT 2011, held in Belfast, ME, USA, in September 2011. The 23 revised full papers were carefully reviewed and selected from 55 submissions. They are organized in topical sections on maps and navigation, spatial change, spatial reasoning, spatial cognition and social aspects of space, perception and spatial semantics, and space and language.