bibtext: @inproceedings{
  wu2024agentkit,
  title={AgentKit: Structured {LLM} Reasoning with Dynamic Graphs},
  author={Yue Wu and Yewen Fan and So Yeon Min and Shrimai Prabhumoye and Stephen Marcus McAleer and Ruslan Salakhutdinov and Yonatan Bisk and Yuanzhi Li and Tom Mitchell},
  booktitle={First Conference on Language Modeling},
  year={2024},
  url={https://openreview.net/forum?id=PKfAq8N4fK}
  }
abstract: We propose an intuitive LLM prompting framework (AgentKit) for multifunctional agents. 
  AgentKit offers a unified framework for explicitly constructing a complex "thought process" from simple natural language prompts. The basic building block in AgentKit is a **node**, containing a natural language prompt for a specific subtask. The user then puts together chains of nodes, in order to build a "thought process" for any problem, like stacking LEGO pieces. The chains of nodes can be designed to explicitly enforce a naturally **structured** "thought process". For example, for the task of writing a paper, one may start with the thought process of 1) identify a core message, 2) identify prior research gaps, etc.
  The nodes in AgentKit can be designed and combined in different ways to implement multiple advanced capabilities including on-the-fly hierarchical planning, reflection, and learning from interactions. 
  In addition, due to the modular nature and the intuitive design to simulate explicit human thought process, a basic agent could be implemented as simple as a list of prompts for the subtasks and therefore could be designed and tuned by someone *without any programming experience*. Quantitatively, we show that agents designed through AgentKit achieve SOTA performance on Webshop and Crafter. These advances underscore AgentKit's potential in making LLM agents effective and accessible for a wider range of applications.
title: AgentKit: Structured LLM Reasoning with Dynamic Graphs
authors: Yue Wu Yewen Fan So Yeon Min Shrimai Prabhumoye Stephen Marcus McAleer Ruslan Salakhutdinov Yonatan Bisk Yuanzhi Li Tom Mitchell