[FEATURE] Large Language Models for Algorithm Design Platform #79
Description
Feature Description
Feature Description
LLM4AD is an open-source, modular, and user-friendly platform designed for automatic algorithm development leveraging large language models (LLMs). With DeepSeek models as the default LLMs, the platform empowers users to streamline algorithm design processes efficiently.
Website: http://www.llm4ad.com/
Repository: https://github.com/Optima-CityU/llm4ad
Documentation: https://llm4ad-doc.readthedocs.io/en/latest/ Explore LLM4AD to harness the power of LLMs for innovative algorithm design!
Target Project
llm_for_algorithm_design
Project Directory
starter_ai_agents
Motivation
• Silos suck. Methods from scientific discovery, combinatorial optimization, and ML are often developed in isolation.
• Real-world problems are hybrid. They need a combination of these approaches, not just one.
• Reinventing the wheel is inefficient. Building algorithms from scratch for each new hybrid challenge is slow.
Proposed Solution
We developed a novel llm based platform for algorithm design that synergistically combines methods and problems from scientific discovery, combinatorial optimization, and intelligent agents in machine learning.
User Impact
• Democratizes Advanced Methods: Lowers the barrier to entry, allowing users without deep expertise in all three fields to still build sophisticated hybrid algorithms.
• Fosters Innovation: The platform acts as an "idea incubator," enabling users to experiment with unconventional combinations of techniques that would be otherwise impractical to try.
• Increases Efficiency: Eliminates the grunt work of stitching together disparate libraries, letting users focus on the high-level design and logic of their solutions.
Alternatives Considered
We evaluated two common approaches:
- Manual Design by Experts: Slow and limited by human cognitive bias.
- AutoML/Genetic Programming: Computationally expensive "brute-force" search.
Our LLM-powered platform is superior:
It uses Large Language Models for intelligent, guided algorithm creation. Unlike manual methods, it automates exploration at scale. Unlike AutoML, it uses semantic reasoning to propose novel designs efficiently, moving beyond brute-force search.
Screenshots/Mockups
Please see README.md for more details.
Implementation Checklist
- I have searched for similar feature requests
- I have provided a detailed description of the feature
- I have explained the motivation and user impact
- I have considered alternative solutions