programming environment. Specifically, the agent-based plugin Physarealm was investigated. Physarealm - Agent-based simulations for designers Physarealm is an algorithmic modeling tool utilized within the matrix of Grasshopper. It was created to mimic and observe behaviors of the natural phenomena found within Physarum Polycephalum. Physarum Polycephalum is a biological organism whose behavior has been noted to produce networks of efficiency between between food placement. This behavior can be greatly conducive to solving certain spatial questions when trying to span between defined locations (from emitter to food source). By mimicking P. Polycephalum biological processes, Physarealm functions mainly as a tool for spatial analysis, but also has capabilities of rapid form production. These capabilities will be analyzed further throughout this paper through various experiments. The plugin first works within an established environment (BREP, box, or surface) and places agents throughout seeking to reach the food source in the most efficient way possible (see Fig. 6). Several output visualization options are available to the designer to help translate varied agent behavior. Physarealm utilizes a stigmergic algorithmic process which essentially generates either a 2D or 3D latticework grid system, giving agents locations to move within the system. Various amounts of chemo-attractor is then embedded throughout the lattice system, thus providing the means and method of communication between various agents, thus also simulating certain processes found within the ant colony optimization algorithm.
Trails and agents, over time, seek out the most efficient pathway possible in order to locate food sources. It is important to note that although the Physarealm algorithm was created to mimic P. Polycephalum processes, it can be further modified to function as an ant-based behavior analyzer. Meaning success is not necessarily contributed to finding the shortest possible route initially, but overtime to highlight more desirable passageways.
Figure 6. All Physarealm components and typical workflow
Architectural Relevance Conventional P. Polycephalum, and Ant Colony Optimization tests have been best tested and understood within the 2D realm. Typical 2D testing situations involve finding the best pathway for specific circumstances. Physarealm adds much needed strength to these tests by expanding testing options into the third dimension. As can be seen in the previous image, options are available to explore box, BREP, or surface environments. These options add incredible value to spatial designers seeking to solve unique 3D problems. As a tool for designers, Physarealm provides a powerful framework for massive amounts of exploration for diverse design solutions. Explored in this paper are the possibilities merited by Physarealm to solve architectural problems such as circulation patterns, egress solutions, form finding strategies, and