Design is an important research topic in engineering and architecture, since design is not only a means of change but also one of the keystones of economic competitiveness and the fundamental precursor to manufacturing. However, our understanding of design as a process and our ability to model it are still very limited. The development of computational models founded on the artificial intelligence paradigm has provided an impetus for much of current design research -- both computational and cognitive. Notwithstanding their immaturity noticeable advances have been made both in extending our understanding of design and in developing tools based on that understanding. The papers in this volume are from the Third International Conference on Artificial Intelligence in Design held in August 1994 in Lausanne, Switzerland. They represent 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 aid designers.

One of the foundations for change in our society comes from designing. Its genesis is the notion that the world around us either is unsuited to our needs or can be improved. The need for designing is driven by a society's view that it can improve or add value to human existence well beyond simple subsistence. As a consequence of designing the world which we inhabit is increasingly a designed rather than a naturally occurring one. In that sense it is an "artificial" world. Designing is a fundamental precursor to manufacturing, fabrication, construction or implementation. Design research aims to develop an understanding of designing and to produce models of designing that can be used to aid designing. Artificial intelligence has provided an environmental paradigm within which design research based on computational constructions, can be carried out. Design research can be carried out in variety of ways. It can be viewed as largely an empirical endeavour in which experiments are designed and executed in order to test some hypothesis about some design phenomenon or design behaviour. This is the approach adopted in cognitive science. It often manifests itself through the use of protocol studies of designers. The results of such research form the basis of a computational model. A second view is that design research can be carried out by positing axioms and then deriving consequences from them.

Change is one of the most significant parameters in our society. Designers are amongst the primary change agents for any society. As a consequence design is an important research topic in engineering and architecture and related disciplines, since design is not only a means of change but is also 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 much of current design research -both computational and cognitive. These forms of design research have only been carried out in the last decade or so and in the temporal sense they are still immature. Notwithstanding this immaturity, noticeable advances have been made both in extending our understanding of design and in developing tools based on that understanding. Whilst many researchers in the field of artificial intelligence in design utilise ideas about how humans design as one source of concepts there is normally no attempt to model human designers. Rather the results of the research presented in this volume demonstrate approaches to increasing our understanding of design as a process.

Designing is one of the foundations for change in our society. It is a fundamental precursor to manufacturing, fabrication and construction. Design research aims to develop an understanding of designing and to produce models of designing that can be used to aid designing. The papers in this volume are from the Sixth International Conference on Artificial Intelligence in Design (AID'00) held in June 2000, in Worcester, Massachusetts, USA. They represent the state of the art and the cutting edge of research and development in this field, and demonstrate both the depth and breadth of the artificial intelligence paradigm in design. They point the way for the development of advanced computer-based tools to aid designers, and describe advances in both theory and application. This volume will be of particular interest to researchers, developers, and users of advanced computer systems in design.

The development of computational models of design founded on the artificial intelligenceparadigm has provided an impetus for muchofcurrentdesign research. As artificial intelligence has matured and developed new approaches so the impact ofthese new approaches on design research has been felt. This can be seen in the wayconcepts from cognitive science has found theirway into artificial intelligence and hence into design research. And, also in the way in which agent-based systems arebeingincorporated into design systems. In design research there is an increasing blurring between notions drawn from artificial intelligence and those drawn from cognitive science. Whereas a number of years ago the focus was largely on applying artificial intelligence to designing as an activity, thus treating designing as a form ofproblem solving, today we are seeing a much wider variety ofconceptions of the role of artificial intelligence in helping to model and comprehend designing as a process. Thus, we see papers in this volume which have as their focus the development or implementationofframeworks for artificial intelligence in design - attempting to determine a unique locus for these ideas. We see papers which attempt to find foundations for the development of tools based on the artificial intelligence paradigm; often the foundations come from cognitive studiesofhuman designers.

In the areas of industry and engineering, AI techniques have become the norm in sectors including computer-aided design, intelligent manufacturing, and control. Papers in this volume represent work by both computer scientists and engineers separately and together. They directly and indirectly represent a real collaboration between computer science and engineering, covering a wide variety of fields related to intelligent systems technology ranging from neural networks, knowledge acquisition and representation, automated scheduling, machine learning, multimedia, genetic algorithms, fuzzy logic, robotics, automated reasoning, heuristic searching, automated problem solving, temporal, spatial and model-based reasoning, clustering, blackboard architectures, automated design, pattern recognition and image processing, automated planning, speech recognition, simulated annealing, and intelligent tutoring, as well as various computer applications of intelligent systems including financial analysis, artificial

This five-volume set clearly manifests the great significance of these key technologies for the new economies of the new millennium. The discussions provide a wealth of practical ideas intended to foster innovation in thought and, consequently, in the further development of technology. Together, they comprise a significant and uniquely comprehensive reference source for research workers, practitioners, computer scientists, academics, students, and others on the international scene for years to come.

This book constitutes the refereed proceedings of the First International Conference on Case-Based Reasoning, ICCBR-95, held in Sesimbra, Portugal, in October 1995. The 52 revised papers included are classified as scientific papers , application papers , and posters . All current aspects of research and development aiming at industrial applications in CBR are addressed. Among the topical sections are case and knowledge representation, case retrieval, nearest neighbour methods, case adaption and learning, cognitive modelling, integrated reasoning methods, and application-oriented methods: planning, decision making, diagnosis, interpretation, design, etc.

Design is believed to be one of the most interesting and challenging problem-solving activities ever facing artificial intelligence (AI) researchers. Knowledge-based systems using rule-based and model-based reasoning techniques have been applied to build design automation and/or design decision support systems. Although such systems have met with some success, difficulties have been encountered in terms of formalizing such generalized design experiences as rules, logic, and domain models. Recently, researchers have been exploring the idea of using case-based reasoning (CBR) techniques to complement or replace other approaches to design support. CBR can be considered as an alternative to paradigms such as rule-based and model-based reasoning. Rule-based expert systems capture knowledge in the form of if-then rules which are usually identified by a domain expert. Model-based reasoning aims at formulating knowledge in the form of principles to cover the various aspects of a problem domain. These principles, which are more general than if-then rules, comprise a model which an expert system may use to solve problems. Model-based reasoning (MBR) is sometimes called reasoning from first principles. Instead of generalizing knowledge into rules or models, CBR is an experience-based method. Thus, specific cases, corresponding to prior problem-solving experiences, comprise the main knowledge sources in a CBR system. This volume includes a collection of chapters that describe specific projects in which case-based reasoning is the focus for the representation and reasoning in a particular design domain. The chapters provide a broad spectrum of applications and issues in applying and extending the concept of CBR to design. Each chapter provides its own introduction to CBR concepts and principles.