  Foundation model-enabled generative artificial intelligence facilitates the
development and implementation of agents, which can leverage distinguished
reasoning and language processing capabilities to takes a proactive, autonomous
role to pursue users' goals. Nevertheless, there is a lack of systematic
knowledge to guide practitioners in designing the agents considering challenges
of goal-seeking (including generating instrumental goals and plans), such as
hallucinations inherent in foundation models, explainability of reasoning
process, complex accountability, etc. To address this issue, we have performed
a systematic literature review to understand the state-of-the-art foundation
model-based agents and the broader ecosystem. In this paper, we present a
pattern catalogue consisting of 17 architectural patterns with analyses of the
context, forces, and trade-offs as the outcomes from the previous literature
review. The proposed catalogue can provide holistic guidance for the effective
use of patterns, and support the architecture design of foundation model-based
agents by facilitating goal-seeking and plan generation.
