Gameplay in real-time strategy games seems somehow to be confined to a de facto standard where economical micro-management is equally important as combat strategy, if not more important. To enable stronger combat-oriented gameplay without sacrificing other key aspects of the genre, we propose an automated system for scheduling unit training, which we believe may allow the exploration of new paradigms of play. To be accepted by the player, such a system must, among other things, be efficient and reliable, which is a non-trivial task considering the highly dynamic nature of the environment in this genre of games. To overcome such a challenge, we propose a system inspired in the swarm intelligence demonstrated by social insects, namely wasps, and describe its limitations and benefits, based on the evaluation of an implementation of the approach as a modification of the game Warcraft III The Frozen Throne (Blizzard Entertainment, 2003).

GENE_ARCH is a Generative Design System that combines Pareto Genetic Algorithms with an advanced energy simulation engine. This work explores its integration with a Shape Grammar, acting as GENE_ARCH’s shape generation module. The islamic patio house typology is readdressed in a contemporary context, by improving its energy-efficiency, and rethinking its role in the genesis of high-density urban areas, while respecting its specific spatial organization and cultural grounding. Field work was carried out in Marrakesh, surveying a number of patio houses, becoming the Corpus of Design, from where a shape grammar was generated. The computational implementation of the patio house grammar was done within GENE_ARCH. The resulting program was able to generate new, alternative patio houses designs that were more energy efficient, while respecting the traditional rules captured from the analysis of existing houses. After the computational system was fully implemented, it was possible to realise a large number of experiments. The first experiments kept more restrained rules, thus generating new designs that closer resembled the existing ones. The progressive relaxation of rules and constraints allowed for a larger number of variations to emerge. Analysis of energy results provide insight into the main patterns resulting from the GA search processes.