Saving energy is a major concern. Hence, it is fundamental to design and construct buildings that are energy-efficient. It is known that the early stage of architectural design has a significant impact on this matter.
However, it is complex to create designs that are optimally energy efficient, and at the same time balance other essential criterias such as economics, space, and safety. One state-of-the art approach is to create parametric designs, and use a genetic algorithm to optimize
across different objectives. We further improve this method, by aggregating the solutions of multiple agents. We evaluate diverse teams, composed by different agents; and uniform teams, composed by multiple copies of a single agent. We test our approach across three design cases of increasing complexity, and show that the diverse team provides a significantly larger percentage
of optimal solutions than single agents.