Reinforcement learning algorithm search

US12430551B2 · kind B2 · utility

Assignee

• Google LLC · US

Inventors

• John Dalton Co-Reyes · San Francisco, US
• Yingjie Miao · Menlo Park, US
• Daiyi Peng · Cupertino, US
• Sergey Levine · Redmond, US
• Quoc V. Le · Stanford, US
• Honglak Lee · Mountain View, US
• Aleksandra Faust · Palo Alto, US

Key dates

• Filing date: Jun 3, 2021
• Grant date: Sep 30, 2025
• Expiry date: Jun 6, 2044

Classification

• Technology area (CPC G): Physics
• CPC primary: G06N3/092
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

Methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for generating and searching reinforcement learning algorithms. In some implementations, a computer-implemented system generates a sequence of candidate reinforcement learning algorithms. Each candidate reinforcement learning algorithm in the sequence is configured to receive an input environment state characterizing a state of an environment and to generate an output that specifies an action to be performed by an agent interacting with the environment. For each candidate reinforcement learning algorithm in the sequence, the system performs a performance evaluation for a set of a plurality of training environments. For each training environment, the system adjusts a set of environment-specific parameters of the candidate reinforcement learning algorithm by performing training of the candidate reinforcement learning algorithm to control a corresponding agent in the training environment. The system generates an environment-specific performance metric for the candidate reinforcement learning algorithm that measures a performance of the candidate reinforcement learning algorithm in …