Readings In Qualitative Reasoning About Physical Systems

Readings in Qualitative Reasoning about Physical Systems describes the automated reasoning about the physical world using qualitative representations. This text is divided into nine chapters, each focusing on some aspect of qualitative physics. The first chapter deal with qualitative physics, which is concerned with representing and reasoning about the physical world. The goal of qualitative physics 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. The succeeding chapter discusses the qualitative calculus and its role in constructing an envisionment that includes behavior over both mythical time and elapsed time. These topics are followed by reviews of the mathematical aspects of qualitative reasoning, history-based simulation and temporal reasoning, as well as the intelligence in scientific computing. The final chapters are devoted to automated modeling for qualitative reasoning and causal explanations of behavior. These chapters also examine the qualitative kinematics of reasoning about shape and space. This book will prove useful to psychologists and psychiatrists.

Readings in Qualitative Reasoning about Physical Systems describes the automated reasoning about the physical world using qualitative representations. This text is divided into nine chapters, each focusing on some aspect of qualitative physics. The first chapter deal with qualitative physics, which is concerned with representing and reasoning about the physical world. The goal of qualitative physics 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. The succeeding chapter discusses the qualitative calculus and its role in constructing an envisionment that includes behavior over both mythical time and elapsed time. These topics are followed by reviews of the mathematical aspects of qualitative reasoning, history-based simulation and temporal reasoning, as well as the intelligence in scientific computing. The final chapters are devoted to automated modeling for qualitative reasoning and causal explanations of behavior. These chapters also examine the qualitative kinematics of reasoning about shape and space. This book will prove useful to psychologists and psychiatrists.

This book deals with a key area of industrial robotics ? the automation of small batch assembly. Assembly imparts enormous added value but turns out to be extraordinarily difficult to automate. The work presented here, all from the Centre for Intelligent Systems at the University of Wales, Aberystwyth, addresses this issue and shows ways in which the difficulties may be reduced through systematic architectural designs and specific structures for interfacing and controlling sensory-actuation systems. The book develops three main themes: a task-centred approach to robotic assembly, explicit reasoning techniques for fault diagnosis and error handling; and sensor-actuator integration methods. These are vital topics for those concerned with flexible automation and robotics.

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.

These twenty-eight contributions report advances in one of the most active research areas in artificial intellgence. Qualitative modeling techniques are an essential part of building second generation knowledge-based systems. This book provides a timely overview of the field while also giving some indications about applications that appear to be feasible now or in the near future. Chapters are organized into sections covering modeling and simulation, ontologies, computational issues, and qualitative analysis. Modeling a physical system in order to simulate it or solve particular problems regarding the system is an important motivation of qualitative physics, involving formal procedures and concepts. The chapters in the section on modeling address the problem of how to set up and structure qualitative models, particularly for use in simulation. Ontology, or the science of being, is the basis for all modeling. Accordingly, chapters on ontologies discuss problems fundamental for finding representational formalism and inference mechanisms appropriate for different aspects of reasoning about physical systems. Computational issues arising from attempts to turn qualitative theories into practical software are then taken up. In addition to simulation and modeling, qualitative physics can be used to solve particular problems dealing with physical systems, and the concluding chapters present techniques for tasks ranging from the analysis of behavior to conceptual design.

Design has now become an important research topic in engineering and architecture. Design is one of the keystones to economic competitiveness and the fundamental precursor to manufacturing. The development of computational models founded on the artificial intelligence paradigm has provided an impetus for current design research. This volume contains contributions from the Second International Conference on Artificial Intelligence in Design held in June 1992 in Pittsburgh. They represent the state-of-the-art and the cutting edge of research and development in this field. They are of particular interest to researchers, developers and users of computer systems in design. This volume demonstrates both the breadth and depth of artificial intelligence in design and points the way forward for our understanding of design as a process and for the development of computer-based tools to aiddesigners.

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 symposium had two main aims, to investigate the state-of-the-art in the application of artificial intelligence techniques in real-time control, and to bring together control system specialists, artificial intelligence specialists and end-users. Many professional engineers working in industry feel that the gap between theory and practice in applying control and systems theory is widening, despite efforts to develop control algorithms. Papers presented at the meeting ranged from the theoretical aspects to the practical applications of artificial intelligence in real-time control. Themes were: the methodology of artificial intelligence techniques in control engineering; the application of artificial intelligence techniques in different areas of control; and hardware and software requirements. This symposium showed that there exist alternative possibilities for control based on artificial intelligence techniques.