System and method for multi-type mean field reinforcement machine learning
US12327167B2 · kind B2 · utility
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Key dates
| Filing date | Feb 28, 2020 |
| Grant date | Jun 10, 2025 |
| Priority date | — |
| Expiry date | Dec 13, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A system for a machine reinforcement learning architecture for an environment with a plurality of agents includes: at least one memory and at least one processor configured to provide a multi-agent reinforcement learning architecture, the multi-agent reinforcement learning model based on a mean field Q function including multiple types of agents, wherein each type of agent has a corresponding mean field.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.