Multi-agent reinforcement learning with matchmaking policies
US11627165B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 24, 2020 |
| Grant date | Apr 11, 2023 |
| Priority date | — |
| Expiry date | Sep 4, 2041 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L63/205
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a policy neural network having a plurality of policy parameters and used to select actions to be performed by an agent to control the agent to perform a particular task while interacting with one or more other agents in an environment. In one aspect, the method includes: maintaining data specifying a pool of candidate action selection policies; maintaining data specifying respective matchmaking policy; and training the policy neural network using a reinforcement learning technique to update the policy parameters. The policy parameters define policies to be used in controlling the agent to perform the particular task.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.