RAO uses RL to train recursive agents that delegate sub-tasks to self-copies, yielding better training efficiency, generalization to harder tasks, scaling beyond context windows, and lower wall-clock time.
- Returns: Dict of {item_name: count} - Example: inv = view_inventory()
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Recursive Agent Optimization
RAO uses RL to train recursive agents that delegate sub-tasks to self-copies, yielding better training efficiency, generalization to harder tasks, scaling beyond context windows, and lower wall-clock time.