Self-organizing sequential memory pattern machine and reinforcement learning method
US8504493B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Feb 15, 2011 |
| Grant date | Aug 6, 2013 |
| Priority date | — |
| Expiry date | Jan 13, 2032 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A self-organizing computing machine utilizes a method for mapping from a plurality of patterns contained within provided inputs to an invariant perception, distinguishable by a name or a label. The self-organizing computing machine includes a network of at least three nodes arranged in at least two hierarchical levels, at least one feature extractor, and at least one output unit arranged to interface the invariant perception. The nodes may include a reinforcement learning sub-network combined with an ensemble learning sub-network. The reinforcement learning sub-network may be arranged to receive at least two correlants, to determine a plurality of output values and to output the output values to the nodes of the higher level and the nodes of the lower level. Also, the ensemble learning sub-network may be arranged to receive and to combine output values from nodes of the higher level and nodes of the lower level.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.