Amazon Technologies, Inc.

Pratik Anil Chaudhari

Stefano Soatto

Alexander Johannes Smola

Rasool Fakoor

Techniques for Meta-Q-Learning (MQL) are described. A method of MQL may include receiving a request from an agent to perform adaptation based at least on task data associated with a new task collected by the agent, identifying a subset of meta-training data corresponding to the task data in a replay buffer, and adapting a policy using the subset of meta-training data and the task data to generate an adapted policy, wherein the adapted policy is used identify a next action for the agent to perform.

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Pasadena, CA, United States of America

Pratik Anil Chaudhari