This paper presents a novel computer-aided design system which uses a computational approach to producing 3D images for stimulating creativity of designers. It introduces the genetic algorithm first. Then a binary tree based genetic algorithm is presented. This approach is illustrated by a 3D image generative example, which uses complex function expressions as chromosomes to form a binary tree, and all genetic operations are performed on the binary tree. Corresponding complex functions are processed by MATLAB software to form 3D images of artistic flowers. This generative design is integrated with a visualization interface, which allows designers to interact and select from instances for design evolution. It shows the system is able to enhance the possibility of discovering various potential design solutions.

This paper presents a context-aware multi-agent cooperative design system framework. It analyses the related work of multi-agent cooperative design system and context-awareness computing first. Then, it presents the architecture of a multi-agent cooperative design system and the structure of a design agent in cooperative environment. Subsequently, it introduces the XML-based context modelling, capturing and processing in the environment. Finally, the design process is illustrated by a gear reducer design instance. The purpose of the paper is to bridge pervasive computing with agents through context-awareness and apply it in cooperative design.

Design is a complex problem solving and knowledge refinement process. Learning is a part of this process that can improve computer based design support systems by using the knowledge representing the experience and expertise of designers. Learning from past design examples, and acquiring new knowledge during the process of design are closely related activities that must be supported by future computer supported design systems. This paper analyses the relation between design and learning activity to propose a learning model of design first. Then it presents the software architecture of a design agent with an inductive learning mechanism. Subsequently it introduces the knowledge representation and learning algorithms in a multi-agent design system. Finally, the paper examines the possible ways in which the proposed learning model and the software architecture can be placed in an industrial and engineering design context for developing application tools for design support.

New architectures for next-generation of computer-aided design environments need to be distributed, evolutive, and cooperative. This paper presents a multi-agent design environment that supports cooperative and evolutionary design by cooperation of a group of agents. Multi-agent system architecture offers a promising framework with its novel approach for dynamically creating and managing agent communities in widely distributed and ever-changing design environments; while the genetic algorithm based approach provides a foundation for supporting evolutionary and innovative design abilities. The computational and information processing processes involved in evolutionary and distributed environment are discussed in this paper.

In product design, sketches and images are strong devices for stimulating creativity. This paper presents a novel visual evolutionary computing environment to provide support for creative design. The 2D sketches and 3D images can be generated by combination of evolutionary computing technology and visualization technology in this environment. A tree-based genetic algorithm is illustrated by a reading lamp design example, which uses genetic algorithm with binary mathematical expression tree to form 2D sketches and programming using Visual Ctt6.0 and ACIS to generate 3D images. It shows that the approach is able to generate some creative solutions and demonstrates the potential of computational approach in creative design.