  The rapid advancement of AI technology has led to widespread applications of
agent systems across various domains. However, the need for detailed
architecture design poses significant challenges in designing and operating
these systems. This paper introduces a taxonomy focused on the architectures of
foundation-model-based agents, addressing critical aspects such as functional
capabilities and non-functional qualities. We also discuss the operations
involved in both design-time and run-time phases, providing a comprehensive
view of architectural design and operational characteristics. By unifying and
detailing these classifications, our taxonomy aims to improve the design of
foundation-model-based agents. Additionally, the paper establishes a decision
model that guides critical design and runtime decisions, offering a structured
approach to enhance the development of foundation-model-based agents. Our
contributions include providing a structured architecture design option and
guiding the development process of foundation-model-based agents, thereby
addressing current fragmentation in the field.
