Recursive Agent Optimization
Recursive Agent Optimization (RAO) trains a single large language model to become a 'meta-agent' capable of spawning and delegating sub-tasks to new instances of itself. This teaches agents how to use recursion for better scaling, generalization, and faster problem-solving compared to single agents.