Agent Design Pattern Catalogue: A Collection of Architectural Patterns for Foundation Model based Agents
<|reference_start|>Agent Design Pattern Catalogue: A Collection of Architectural Patterns for Foundation Model based Agents: 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.<|reference_end|>
@article{liu2024agent,
    title={Agent Design Pattern Catalogue: A Collection of Architectural Patterns
  for Foundation Model based Agents},
    author={Yue Liu, Sin Kit Lo, Qinghua Lu, Liming Zhu, Dehai Zhao, Xiwei Xu,
  Stefan Harrer, Jon Whittle},
    journal={arXiv preprint arXiv:2405.10467},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.10467},
    primaryClass={cs.AI cs.SE}
}