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WORKSHOP
their design outcomes. The 2D outcomes of agent analyses were then used to produce 3D Mesh configurations using the “Bitmap to Mesh” SketchUp extension. The visualization can be thought of as an assistive technology in design, and could be used in form-finding and conceptual design development (Figure 5). Students were able to generate some very interesting variations on the analytical outcomes of agent simulations, quoting Milla Zlatanova and Konstantina Hristova (both students at the MSc ATC course, Sofia): “Agent-based simulations could be perceived not only as a methodology to explore environment in terms of habitat but also to implement the outcomes in a conceptual development of a project. The graphical representation of movement suggests a substantial source of inspiration. For example, several congested layers of trails with fluctuating parameters would give us nodes and paths to explore and to implement into a future design; a 3D model of the agents’ movement resembles a topography, it could be translated into urban environment or a map of public attractions.”
WORKSHOP 3: HOW CREATIVITY AND EFFICIENCY LINK TO VISIBILITY PERFORMANCE OF LAYOUTS
In this workshop, MSc SDAC students were to assess a set of design proposals for an architectural practice in terms of ‘creativity’ and ‘efficiency’. The judgment is based on their ‘expert knowledge’ as architects. The exercise was scoped to increase students’ selfawareness of what they recognize as ‘creative’ and ‘efficient’, and to test that against potential design performance through agent-based simulations. The experiment was, therefore, intended to increase learners’ self-consciousness of their own judgment criteria and the implications of that on the configurations of their design proposals, attending to how these configurations might restrict or enable circulation and movement in a building layout. Based on the judgment criteria of six participants, the average scores yielded proposal [g] as the most creative design proposal, marking the highest average ‘creativity’ score (C-score), whilst design proposal number [b] was reported as the least creative (Figure 6). The average efficiency scores (E-scores) presented different preferences; students were more in favour of proposal [c] as the most efficient design. Remarkably, the most creative design proposal [g] came up as the least efficient one. These results are compared to visibility graph configurations (through-vision analysis) that is basically the look-up table that cognitive agents use to make choices about where move next (Figure 7). It was noted that design [g], which was chosen as the most creative and least efficient design presented lower average through vision values (i.e. spaces in this design are less interconnected visually). However, design [b] and [c], marking the least creative and most efficient designs respectively corresponded to lower levels of through movement. With that finding, we concluded that the relationship between what students recognized as ‘creative’ and ‘efficient’ designs and the visibility performance of these designs was not discernible. During this exercise, students developed skills to assess designs both subjectively and through evidence-based methods. It would be interesting in the future to compare their evaluation before and after analysing space. It is thought that through spatial analysis, students will develop better appreciation of the value of designing spaces as opposed to designing solid partitions.