By Kimberle Koile (auth.), John S. Gero (eds.)
Artificial intelligence offers an environmentally wealthy paradigm during which layout study in keeping with computational structures could be conducted. This has been one of many foundations for the constructing box referred to as "design computing".
Recently, there was a growing to be curiosity in what designers do once they layout and the way they use computational instruments. This kinds the foundation of a newly emergent box known as "design cognition" that pulls partially on cognitive science.
This new convention sequence goals to supply a bridge among the 2 fields of "design computing" and "design cognition". The papers during this quantity are from the "First overseas convention on layout Computing and Cognition" (DCC'04) held on the Massachusetts Institute of expertise, united states. They characterize state-of-the artwork learn and improvement in layout computing and cognition. they're of specific curiosity to researchers, builders and clients of complex computation in layout and those that have to achieve a greater figuring out of designing.
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Additional info for Design Computing and Cognition ’04
The relationship between a satisfier space and its constituent feature nodes is shown in Figure 3. 3. OPERATIONS The formal symbol level operators for supporting movement in design space are ll"-resolution, indexing and reuse, hysterical undo, design unification and design anti-unification (Burrow and Woodburyl999). At the interaction level, user-driven operations support the construction, navigation and synchronisation moves (Datta et al 2002) during exploration. The feature node enables the designer to access both these types of operations as the Operations of exploration.
Stouffs, R and Krishnamurti R: 2002, Representational flexibility for design, in JS Gero (ed), Artificial Intelligence in Design '02, Kluwer Academic Publishers, pp. 105-128. Summers, J, Lacroix Z, and J Shah: 2002, Case-based design facilitated by the design exemplar, in JS Gero (ed), Artificial Intelligence in Design '02, Kluwer Academic Publishers, pp. 453-476. Veloso, MM, Mulvehill AM, and Cox MT: 1997, Rationale-supported mixed-initiative casebased planning, Innovative Applications of Artificial Intelligence, Providence, RI, pp.
The feature node must capture the connections between a problem and its possible solutions (partial or complete) uncovered in design space. • Choices - Problems and requirements have multiple solutions. In design, a problem formulation may have no solutions, a finite number of solutions or an arbitrarily large collection of solutions. The intentional choices made by the designer in the reformulation of problems and commitment to generated solutions during exploration must be recorded in the feature node representation.