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arxiv:2308.05960

BOLAA: Benchmarking and Orchestrating LLM-augmented Autonomous Agents

Published on Aug 11, 2023
ยท Submitted by akhaliq on Aug 14, 2023
Authors:
,
,
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Ran Xu ,

Abstract

The massive successes of large language models (LLMs) encourage the emerging exploration of LLM-augmented Autonomous Agents (LAAs). An LAA is able to generate actions with its core LLM and interact with environments, which facilitates the ability to resolve complex tasks by conditioning on past interactions such as observations and actions. Since the investigation of LAA is still very recent, limited explorations are available. Therefore, we provide a comprehensive comparison of LAA in terms of both agent architectures and LLM backbones. Additionally, we propose a new strategy to orchestrate multiple LAAs such that each labor LAA focuses on one type of action, i.e. BOLAA, where a controller manages the communication among multiple agents. We conduct simulations on both decision-making and multi-step reasoning environments, which comprehensively justify the capacity of LAAs. Our performance results provide quantitative suggestions for designing LAA architectures and the optimal choice of LLMs, as well as the compatibility of both. We release our implementation code of LAAs to the public at https://github.com/salesforce/BOLAA.

Community

Hi, very interesting paper. What happened to the OSS Code that was supposed to be at https://github.com/salesforce/BOLAA ? I checked the salesforce org, no repos similarly named were available to the public, so where did it go? Or has it not been released yet? Thank you for answering.

Paper author

Hi @mharris021 , thanks for your interest in the work! We've completed the legal review and have now made the initial code public. You can access it at: https://github.com/salesforce/BOLAA.

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