Mary Lou Maher

Muthaukumar Balachandran

Dong Mei Zhang

First Published in 1995. Routledge is an imprint of Taylor & Francis, an informa company.

Case-based Reasoning in Design

Adrian David Cheok

Norbert Streitz

Hamid Aghajan

Juan Carlos Augusto

Reiner Wichert

David Keyson

Gwenn Englebienne

Ben Kröse

This book constitutes the refereed proceedings of the Second International Joint Conference on Ambient Intelligence, AmI 2011, held in Amsterdam, The Netherlands, in November 2011. The 58 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers cover a wide range of topics such as haptic interfaces, smart sensing, smart environments, novel interaction technologies, affecting human behaviour, privacy and trust, landscape and ambient assisted living.

Second International Joint Conference, AmI 2011, Amsterdam, The Netherlands, November 16-18, 2011, Proceedings

Ambient Intelligence

John S. Gero

First Published in 1993. Routledge is an imprint of Taylor & Francis, an informa company.

Modeling Creativity and Knowledge-based Creative Design

HI-RISE--a Knowledge-based Expert System for the Preliminary Structural Design of High Rise Buildings

John Steven Gero

Reprints of International Conference of Computational and Cognitive Models of Creative Design VI, Heron Island, Australia, 10-14 December 2005

Computational and Cognitive Models of Creative Design VI

Lina Lee

Interactive technology is increasingly integrated with physical objects that do not have a traditional keyboard and mouse style of interaction, and many do not even have a display. These objects require new approaches to interaction design, referred to as post-WIMP (Windows, Icons, Menus, and Pointer) or as embodied interaction design. This book provides an overview of the design opportunities and issues associated with two embodied interaction modalities that allow us to leave the traditional keyboard behind: tangible and gesture interaction. We explore the issues in designing for this new age of interaction by highlighting the significance and contexts for these modalities. We explore the design of tangible interaction with a reconceptualization of the traditional keyboard as a Tangible Keyboard, and the design of interactive three-dimensional (3D) models as Tangible Models. We explore the design of gesture interaction through the design of gesture-base commands for a walk-up-and-use information display, and through the design of a gesture-based dialogue for the willful marionette. We conclude with design principles for tangible and gesture interaction and a call for research on the cognitive effects of these modalities.

Designing for Gesture and Tangible Interaction

Kathryn E. Merrick

Motivated learning is an emerging research field in artificial intelligence and cognitive modelling. Computational models of motivation extend reinforcement learning to adaptive, multitask learning in complex, dynamic environments – the goal being to understand how machines can develop new skills and achieve goals that were not predefined by human engineers. In particular, this book describes how motivated reinforcement learning agents can be used in computer games for the design of non-player characters that can adapt their behaviour in response to unexpected changes in their environment. This book covers the design, application and evaluation of computational models of motivation in reinforcement learning. The authors start with overviews of motivation and reinforcement learning, then describe models for motivated reinforcement learning. The performance of these models is demonstrated by applications in simulated game scenarios and a live, open-ended virtual world. Researchers in artificial intelligence, machine learning and artificial life will benefit from this book, as will practitioners working on complex, dynamic systems – in particular multiuser, online games.

Curious Characters for Multiuser Games

Motivated Reinforcement Learning

Over the last decade research into design processes utilizing ideas and models drawn from artificial intelligence has resulted in a better understanding of design -- particularly routine design -- as a process. Indeed, most of the current research activity directly or indirectly deals only with routine design. Not surprisingly, many practicing designers state that the level of understanding represented by these models is only of mild interest because they fail to embody any ideas about creativity. This volume provides a set of chapters in the areas of modeling creativity and knowledge-based creative design that examines the potential role and form of computer-aided design which supports creativity. It aims to define the state-of-the-art of computational creativity in design as well as to identify research directions. Published at a time when the field of computational creativity in design is still immature, it should influence the directions of growth and assist the field in reaching maturity.

Modeling Creativity and Knowledge-Based Creative Design

Pearl Pu

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.

Issues and Applications of Case-Based Reasoning to Design

Mary Lou Maher

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