Agent Design Pattern Catalogue: A Collection of Architectural Patterns for Foundation Model based Agents
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866916469723365376 |
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| author | Liu, Yue Lo, Sin Kit Lu, Qinghua Zhu, Liming Zhao, Dehai Xu, Xiwei Harrer, Stefan Whittle, Jon |
| author_facet | Liu, Yue Lo, Sin Kit Lu, Qinghua Zhu, Liming Zhao, Dehai Xu, Xiwei Harrer, Stefan Whittle, Jon |
| contents | 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 18 architectural patterns with analyses of the context, forces, and trade-offs as the outcomes from the previous literature review. We propose a decision model for selecting the patterns. 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_10467 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Agent Design Pattern Catalogue: A Collection of Architectural Patterns for Foundation Model based Agents Liu, Yue Lo, Sin Kit Lu, Qinghua Zhu, Liming Zhao, Dehai Xu, Xiwei Harrer, Stefan Whittle, Jon Artificial Intelligence Software Engineering 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 18 architectural patterns with analyses of the context, forces, and trade-offs as the outcomes from the previous literature review. We propose a decision model for selecting the patterns. 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. |
| title | Agent Design Pattern Catalogue: A Collection of Architectural Patterns for Foundation Model based Agents |
| topic | Artificial Intelligence Software Engineering |
| url | https://arxiv.org/abs/2405.10467 |