Royal Bank of Canada
SYSTEM AND METHOD FOR MULTI-TYPE MEAN FIELD REINFORCEMENT MACHINE LEARNING

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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.

Status:
Application
Type:

Utility

Filling date:

28 Feb 2020

Issue date:

3 Sep 2020