IntroductionΒΆ
LLaMEA (Large Language Model Evolutionary Algorithm) is an innovative framework that leverages the power of large language models (LLMs) such as GPT-4 for the automated generation and refinement of metaheuristic optimization algorithms. The framework utilizes a novel approach to evolve and optimize algorithms iteratively based on performance metrics and runtime evaluations without requiring extensive prior algorithmic knowledge. This makes LLaMEA an ideal tool for both research and practical applications in fields where optimization is crucial.
Key Features:
Automated Algorithm Generation: Automatically generates and refines algorithms using GPT-based or similar LLM models.
Performance Evaluation: Integrates seamlessly with the IOHexperimenter for real-time performance feedback, guiding the evolutionary process.
LLaMEA-HPO: Provides an in-the-loop hyper-parameter optimization mechanism (via SMAC) to offload numerical tuning, so that LLM queries focus on novel structural improvements.
Extensible & Modular: You can easily integrate additional models and evaluation tools.
