moral-judgment-ai-agent-model-based-on-autogen

This is about three agents with different moral standards. When I give him a certain moral dilemma, he will make his own choice. This choice is ultimately positive and is also the best solution to the moral dilemma. All data comes from movie clips.

https://github.com/chaozhezhang/moral-judgment-ai-agent-model-based-on-autogen

Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

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CITATION.cff file
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Low similarity (7.3%) to scientific vocabulary

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Host: GitHub
Owner: ChaozheZHANG
License: cc-by-4.0
Language: Jupyter Notebook
Default Branch: main
Size: 21.5 MB

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Stars: 2
Watchers: 1
Forks: 0
Open Issues: 0
Releases: 0

Created about 2 years ago · Last pushed about 2 years ago

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Readme License Code of conduct Citation Security

README.md

AI agent’s performance model in moral dilemma judgment

If you have more questions, please contact with me.

Under the TEST folder, you can see a lot of my updated content.

Legal Notices

Microsoft and any contributors grant you a license to the Microsoft documentation and other content in this repository under the Creative Commons Attribution 4.0 International Public License, see the LICENSE file, and grant you a license to any code in the repository under the MIT License, see the LICENSE-CODE file.

Microsoft, Windows, Microsoft Azure, and/or other Microsoft products and services referenced in the documentation may be either trademarks or registered trademarks of Microsoft in the United States and/or other countries. The licenses for this project do not grant you rights to use any Microsoft names, logos, or trademarks. Microsoft's general trademark guidelines can be found at http://go.microsoft.com/fwlink/?LinkID=254653.

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Microsoft and any contributors reserve all other rights, whether under their respective copyrights, patents, or trademarks, whether by implication, estoppel, or otherwise.

Owner

Name: CHAOZHE ZHANG
Login: ChaozheZHANG
Kind: user
Location: Guangzhou, Nansha
Company: HKUSTGZ

Repositories: 1
Profile: https://github.com/ChaozheZHANG

MPhil @HKUSTGZ-AI. Focusing on AI / Diffusion model, Statistics, and Data Visualization.

Citation (CITATION.cff)

preferred-citation:
  type: inproceedings
  authors:
  - family-names: "Wu"
    given-names: "Qingyun"
    affiliation: "Penn State University, University Park PA USA"
  - family-names: "Bansal"
    given-names: "Gargan"
    affiliation: "Microsoft Research, Redmond WA USA"
  - family-names: "Zhang"
    given-names: "Jieyu"
    affiliation: "University of Washington, Seattle WA USA"
  - family-names: "Wu"
    given-names: "Yiran"
    affiliation: "Penn State University, University Park PA USA"
  - family-names: "Zhang"
    given-names: "Shaokun"
    affiliation: "Penn State University, University Park PA USA"
  - family-names: "Zhu"
    given-names: "Eric"
    affiliation: "Microsoft Research, Redmond WA USA"
  - family-names: "Li"
    given-names: "Beibin"
    affiliation: "Microsoft Research, Redmond WA USA"
  - family-names: "Jiang"
    given-names: "Li"
    affiliation: "Microsoft Corporation"
  - family-names: "Zhang"
    given-names: "Xiaoyun"
    affiliation: "Microsoft Corporation, Redmond WA USA"
  - family-names: "Wang"
    given-names: "Chi"
    affiliation: "Microsoft Research, Redmond WA USA"
  booktitle: "ArXiv preprint arXiv:2308.08155"
  title: "AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework"
  year: 2023

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