Second, ecology is a diverse discipline and each sub-discipline necessarily has its particular simulation methods. First, it is often the case that simulators representing the same system, designed for ostensibly the same purpose, differ in their results with the reasons buried deep within computer code. Yet there are two unresolved problems for ecological studies relying on simulation. Finally, we discuss limitations, as well as future trends and possibilities for ABMS in architecture.Įcology, like many disciplines, commonly relies on simulation to provide insights into the dynamics of complex systems. By describing each of the resulting categories, we provide new insights into the field of ABMS in architecture. Based on this identification, a comprehensive classification for ABMs in architecture is achieved. Subsequently, in each of the ABMs encountered in the selected literature, we identify what entity an agent in the model represents. The classification is based on a reproducible search method capable of incorporating findings from different domain-specific databases to systematically retrieve relevant literature for ABMS in architecture. Based on a systematic literature review, this paper presents a classification for agent-based modeling and simulation (ABMS) in architecture based on the individual entities being modeled as agents. Over the last two decades, the use of agent-based models (ABMs) to model and simulate the dynamics of complex systems has increased significantly among various scientific fields, including architecture.
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