Model-Agnostic Meta-Learning (MAML) for Agents

A method where AI agents are trained to adapt quickly to new tasks using minimal data.

MAML teaches agents general learning strategies, allowing them to fine-tune their behavior across a wide range of scenarios with little retraining.

This is especially useful for agents deployed in constantly changing environments.