Multiagent Debate
Visit WebsiteGeneral Purpose
Open Source
Enhances language models' factual accuracy and reasoning through collaborative multi-agent debates.
About
Multiagent Debate is an approach designed to improve the factual accuracy and reasoning capabilities of language models by facilitating debates among multiple AI agents. By engaging in structured discussions, these agents critique and refine each other's responses, leading to more reliable and accurate outputs. This method draws inspiration from the 'Society of Mind' theory, emphasizing collaborative problem-solving among AI entities.
Features
- Facilitates debates among multiple AI agents to enhance reasoning.
- Improves factual accuracy through collaborative critique.
- Inspired by the "Society of Mind" theory for AI development.
- Applicable to various domains requiring enhanced language model performance.
Tags
Debate Framework
Language Models
Reasoning Enhancement