Greedy Is a Strong Default: Agents as Iterative Optimizers

1. 1Replace random proposal generators with LLM agents in classical optimization algorithms
2. 2Evaluate the performance of LLM agents on discrete, mixed, and continuous tasks
3. 3Analyze the effectiveness of LLM agents in proposing informed candidates
4. 4Integrate LLM agents with classical optimization machinery to improve overall performance

ML researchers and AI engineers can benefit from this approach to improve optimization tasks, and software engineers can implement these methods in various applications

💡 LLM agents can be used as iterative optimizers to improve the performance of classical optimization algorithms

💡 LLM agents can improve classical optimization algorithms by proposing informed candidates