bin123apple/MACM
[NeurIPS 2024] MACM: Utilizing a Multi-Agent System for Condition Mining in Solving Complex Mathematical Problems
MACM helps solve complex mathematical problems by automatically exploring and linking relevant conditions. You input a math problem, and it outputs the solution by iteratively gathering necessary information, mimicking a group of agents collaborating. This is useful for researchers or educators who need to solve a variety of challenging math and logic puzzles efficiently.
No commits in the last 6 months.
Use this if you need a robust, automated system to tackle difficult mathematical or logical reasoning problems across various domains without needing to re-design prompts for each specific problem.
Not ideal if you prefer manual, step-by-step control over the problem-solving process or if your problems are simple enough to be solved with basic prompting methods.
Stars
92
Forks
17
Language
Python
License
—
Category
Last pushed
Jul 24, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/agents/bin123apple/MACM"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
InfinitiBit/graphbit
GraphBit is the world’s first enterprise-grade Agentic AI framework, built on a Rust core with a...
autogluon/autogluon-assistant
Multi-Agent System Powered by LLMs for End-to-end Multimodal ML Automation
pguso/agents-from-scratch
Build AI agents from first principles using a local LLM - no frameworks, no cloud APIs, no...
samholt/L2MAC
🚀 The LLM Automatic Computer Framework: L2MAC
pguso/ai-agents-from-scratch
Demystify AI agents by building them yourself. Local LLMs, no black boxes, real understanding of...