Special Issue: Learning and creativity Part 1

Special Issue Part 1 ~Issue 3! and Part 2 ~Issue 4! of AIEDAM are based on a workshop on Learning and Creativity held at the 2002 conference on Artificial Intelligence in Design, AID ’02 ~www.cad.strath.ac.uk0AID02_workshop0Work shop_webpage.html; Gero, 2002!, the sixth of similar workshops, with the previous five focusing on Machine Learning in Design and being held at AIDs ’92, ’94, ’96, ’98, and ’00 ~Gero, 1992, 2000; Gero & Sudweeks, 1994, 1996, 1998!. The first three workshops also resulted in special issues of AIEDAM ~Maher et al., 1994; Duffy et al., 1996, 1998!. The purpose of the workshop was to explore the subject of learning and creativity. The objective of the workshop was to bring the ideas, experiences, and latest research together and to produce an insightful understanding of the subject of learning and creativity. The workshop itself focused upon two main topics: the nature of learning and creativity, and learning and creativity in computational-based team design. With respect to the first topic, agreement was reached on defining aspects of creativity. Creativity was considered a judgement, and to involve a product, a process, and a situation. Whether a relationship exists between learning and creativity remained undecided. With respect to the second topic, agreement was reached that an agent-based, mutually learning design system can be developed.Agents ~both human and software! can learn from each other.This requires communication, common goals and understanding ~e.g., ontologies!, and knowledge. The basic ethos of the workshop was the stimulus for this special issue. A general call was extended to the AIEDAM community and workshop participants. The position taken and questions raised for the call was that learning and creativity in design are two related activities, but can the interrelations between the activities be defined? What is the nature of these interrelationships? Does creativity necessarily result in new knowledge and0or learning? Can creativity be supported by computational means? Can learning be supported by computational means? If so, can such computational systems support design practice? Can automated design be considered to be creative? Can learning from past design manipulations be considered to be creative? Authors were invited to submit papers discussing their work in relation to these questions and address: