Architectural programming is the research and decision-making process that identifies the scope of work to be designed. Programming is difficult because it involves identifying, collecting, analyzing and updating information from different sources such as engineers, clients, users, consultants, and others. In this paper I propose a computational model for programming and describe its implementation, a tool called PENA that allows a programming expert to represent different processes and people involved in a project using intelligent agents. By delegating responsibility to agents, a programming expert can better organize and manage project data as well as find creative solutions to conflicting issues through agent negotiation. As a proof-of-concept, I show how an agent, called the Arch-Learner, manages adjacencies of rooms in a simple program for a house by clustering them into public and private rooms. I conclude with a discussion of future work and development of PENA.

This paper revisits the particle flow system, a time-based computational tool, which has received a lot of attention from the early pioneers of digital architecture. The use of particle flow systems in architecture enables designers to materialize what they term as site forces which can later be formalized into a building. The methods offered by various designers for using particle flow systems in architecture have kept the discourse purely formal by focusing on the exterior and neglecting the interior. This paper offers a different way of using and conceptualizing particle flow systems in architecture. Shifting the emphasis from the formal, the paper aims to show the potential of using particle flow systems as a parametric model for exploring the spatial organization of an architectural program. This paper also illustrates the application of the proposed computational model, i.e., the particle flow system, by using a case study – the design of a high-rise building in downtown Tel Aviv, Israel.