| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_8a77280b7cd076fb4d00d807c38fbdac |
| classificationCPCAdditional |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N7-01 |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N5-04
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06Q10-087
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N20-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-006
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N20-20 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N5-04
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06Q10-08
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N20-20 |
| filingDate |
2019-10-31-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_0deeb49cd816c06011876371725a2340
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_4186f33d07cd952b19af588090d1d28b
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_c78322e8bd5a2d173406ed6bbc5186b5
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_2469e4d1e159e35af2070af80cbdc912
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_7aad93738abf36f43bf2c01edb766815
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_bc6b9255fe3883dd93d367225c2f3845 |
| publicationDate |
2020-05-07-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
US-2020143291-A1 |
| titleOfInvention |
Hierarchical Clustered Reinforcement Machine Learning |
| abstract |
A system and method for hierarchical, clustered reinforcement learning is disclosed. A plurality of subject objects may be obtained, and a plurality of clusters of the subject objects may be determined. Clustered reinforcement learning may be performed on each cluster, including training a respective cluster agent for the each cluster. A first cluster of the plurality of clusters may be selected for revision based on selection criteria. After selection of the selected first cluster, individual reinforcement learning may be performed on each individual subject object included in the selected first cluster, including training a respective individual agent for the each individual subject object. An action may be controlled based on a result of the hierarchical, clustered reinforcement learning. |
| isCitedBy |
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-11308431-B2
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-11720809-B2
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-115816466-A
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-112597392-A |
| priorityDate |
2018-11-02-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |