wangtao
/
autogen
mirror of https://github.com/microsoft/autogen.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

update (#2178) 

Co-authored-by: AnonymousRepoSub <“shaokunzhang529@outlook.com” >
This commit is contained in:
Shaokun Zhang 2024-03-28 01:11:20 -04:00 committed by GitHub
parent e6237d44a1
commit dd61eaae43
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
1 changed files with 5 additions and 3 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

8
website/blog/2023-12-23-AgentOptimizer/index.mdx
View File

@ -12,10 +12,12 @@ tags: [LLM, research]
**TL;DR:**
Introducing **AgentOptimizer**, a new class for training LLM agents in the era of LLMs as a service.
**AgentOptimizer** is able to prompt LLMs to iteratively optimize function/skills of AutoGen agents according to the historical conversation and performance.
Checkout one implementation for **AgentOptimizer** on [MATH](https://github.com/hendrycks/math) dataset
[here](https://github.com/microsoft/autogen/blob/main/notebook/agentchat_agentoptimizer.ipynb).
More information could be found in the [paper](https://arxiv.org/abs/2402.11359).
More information could be found in:
**Paper**: https://arxiv.org/abs/2402.11359.
**Notebook**: https://github.com/microsoft/autogen/blob/main/notebook/agentchat_agentoptimizer.ipynb.
## Introduction
In the traditional ML pipeline, we train a model by updating its weights according to the loss on the training set, while in the era of LLM agents, how should we train an agent?